Availability of scikit-learn model for runtime python_compiled#

The following metrics measure the ratio between the prediction time for the runtime compare to scikit-learn. It gives an order of magnitude. They are done by setting assume_finite=True (see config_context). The computed ratio is:

\frac{\textit{execution when predicting with a custom ONNX runtime}} {\textit{execution when predicting with scikit-learn (assume\_finite=True)}}

Due to float32 conversion, it may happen than the highest difference is quite high. The proposition a < b \Rightarrow [a] < [b] is usually true and but not true all the time. It is the same after number where rounded to float32, that’s why the result considers the fourth highest difference and not the first three.

Some figures are missing when the number of observations is high. That means the prediction is slow for one of the runtime (ONNX, scikit-learn) and it would take too long to go further. The list of problems can be found in the documentation of function find_suitable_problem. Default values are usually used to create models but other scenarios are defined by build_custom_scenarios and build_custom_scenarios (2). The benchmark can be generated with a command line:

python -m mlprodict validate_runtime --verbose=1 --out_raw=data.csv --out_summary=summary.xlsx --benchmark=1 --dump_folder=. --runtime=python_compiled

The option -se 1 may be used if the process crashes. The command line can also be extended to test only one model or to skip another one. The whole batch takes between 5 and 15 minutes depending on the machine.

Full data: bench_sum_python_compiled.xlsx

…NB#

name

problem

scenario

optim

opset15

onx_nnodes

BernoulliNB

b-cl

default

OK 13/1

22

BernoulliNB

m-cl

default

OK 13/1

22

BernoulliRBM

num-tr

default

CategoricalNB

b-cl

default

ERR: 3prediction

CategoricalNB

m-cl

default

ERR: 3prediction

CategoricalNB

~b-cl-64

default

ERR: 3prediction

CategoricalNB

~m-label

default

ERR: 1training_time

ComplementNB

b-cl

default

ERR: 1training_time

ComplementNB

m-cl

default

ERR: 1training_time

GaussianNB

b-cl

default

OK 13/1

19

GaussianNB

m-cl

default

OK 13/1

19

MultinomialNB

b-cl

default

ERR: 1training_time

MultinomialNB

m-cl

default

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

BernoulliRBM

num-tr

default

NO CONVERTER

CategoricalNB

b-cl

default

ERR: 3prediction

index 7 is out of bounds for axis 1 with size 7

CategoricalNB

m-cl

default

ERR: 3prediction

index 7 is out of bounds for axis 1 with size 7

CategoricalNB

~b-cl-64

default

ERR: 3prediction

index 7 is out of bounds for axis 1 with size 7

CategoricalNB

~m-label

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 3) instead.

ComplementNB

b-cl

default

ERR: 1training_time

Negative values in data passed to ComplementNB (input X)

ComplementNB

m-cl

default

ERR: 1training_time

Negative values in data passed to ComplementNB (input X)

MultinomialNB

b-cl

default

ERR: 1training_time

Negative values in data passed to MultinomialNB (input X)

MultinomialNB

m-cl

default

ERR: 1training_time

Negative values in data passed to MultinomialNB (input X)

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

BernoulliNB

b-cl

default

OK 13/1

1.0.2

1

1

1

1.8e+03

22

9

skl2onnx

1.1

1

1.8e+03

22

9

2

4

1

BernoulliNB

m-cl

default

OK 13/1

1.0.2

1

3

1

1.9e+03

22

9

skl2onnx

1.1

1

1.9e+03

22

9

2

4

1

BernoulliRBM

num-tr

default

1.0.2

1

CategoricalNB

b-cl

default

ERR: 3prediction

1.0.2

1

3

1

CategoricalNB

m-cl

default

ERR: 3prediction

1.0.2

1

4

1

CategoricalNB

~b-cl-64

default

ERR: 3prediction

1.0.2

1

3

1

CategoricalNB

~m-label

default

ERR: 1training_time

1.0.2

-1

-1

-1

ComplementNB

b-cl

default

ERR: 1training_time

1.0.2

ComplementNB

m-cl

default

ERR: 1training_time

1.0.2

GaussianNB

b-cl

default

OK 13/1

1.0.2

1

1.8e+03

19

11

skl2onnx

1.1

1

1.8e+03

19

11

3

3

1

GaussianNB

m-cl

default

OK 13/1

1.0.2

1

1.8e+03

19

11

skl2onnx

1.1

1

1.8e+03

19

11

3

3

1

MultinomialNB

b-cl

default

ERR: 1training_time

1.0.2

MultinomialNB

m-cl

default

ERR: 1training_time

1.0.2

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

BernoulliNB

b-cl

default

OK 13/1

1

1.1

1

1.1

1.2

0.97

1

1

1.1

0.97

1.1

1.1

1.2

1.2

1.2

BernoulliNB

m-cl

default

OK 13/1

1

1.1

1.1

1.1

1.1

0.97

1

1

1.1

1

1.1

1

1.1

1.1

1.1

GaussianNB

b-cl

default

OK 13/1

0.87

0.93

1

1.5

2.1

0.81

0.9

0.9

0.96

0.95

1

1.5

1.5

2

2.1

GaussianNB

m-cl

default

OK 13/1

0.7

0.74

0.84

1.3

1.8

0.68

0.72

0.71

0.77

0.8

0.88

1.3

1.3

1.8

1.8

AdaBoost#

name

problem

scenario

optim

opset15

onx_nnodes

AdaBoostClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

23

AdaBoostClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

95

AdaBoostClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

95

AdaBoostClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/1

23

AdaBoostRegressor

b-reg

default

OK 15/1

23

AdaBoostRegressor

~b-reg-64

default

OK 15/1

23

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

AdaBoostClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

2

2.3e+03

23

8

skl2onnx

1.1

1

2.3e+03

23

8

3

3

1

1

3

-1

AdaBoostClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

1.2e+04

95

10

skl2onnx

1.1

1

8.6e+03

71

10

12

30

10

1

3

-1

AdaBoostClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

1.2e+04

95

10

skl2onnx

1.1

1

8.6e+03

71

10

12

30

10

1

3

-1

AdaBoostClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/1

1.0.2

2

2.4e+03

23

8

skl2onnx

1.1

1

2.4e+03

23

8

3

3

1

1

3

1

AdaBoostRegressor

b-reg

default

OK 15/1

1.0.2

11

1.1e+04

23

7

skl2onnx

1.1

1

1.1e+04

23

7

1

1.5e+02

10

3

1

-1

AdaBoostRegressor

~b-reg-64

default

OK 15/1

1.0.2

11

1.3e+04

23

7

skl2onnx

1.1

1

1.3e+04

23

7

1

1.5e+02

10

3

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

AdaBoostClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.86

0.84

0.87

0.98

1.2

0.83

0.89

0.82

0.87

0.83

0.93

0.96

1

1.2

1.2

AdaBoostClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.71

0.7

0.74

0.82

1

0.7

0.72

0.69

0.72

0.73

0.76

0.81

0.83

1

1.1

AdaBoostClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.72

0.71

0.74

0.81

0.99

0.71

0.73

0.7

0.72

0.73

0.76

0.8

0.83

0.98

1

AdaBoostClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/1

0.85

0.85

0.89

1.1

1.4

0.83

0.88

0.82

0.87

0.85

0.93

1.1

1.1

1.4

1.4

AdaBoostRegressor

b-reg

default

OK 15/1

0.4

0.42

0.48

0.66

1

0.39

0.42

0.41

0.43

0.47

0.5

0.66

0.66

1

1

AdaBoostRegressor

~b-reg-64

default

OK 15/1

0.39

0.4

0.46

0.67

1.1

0.38

0.4

0.38

0.42

0.44

0.48

0.65

0.69

1.1

1.1

AdditiveChi2Sampler#

name

problem

scenario

optim

opset15

onx_nnodes

AdditiveChi2Sampler

num-tr

default

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

AdditiveChi2Sampler

num-tr

default

ERR: 1training_time

Negative values in data passed to X in AdditiveChi2Sampler.fit

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

AdditiveChi2Sampler

num-tr

default

ERR: 1training_time

1.0.2

AffinityPropagation#

name

problem

scenario

optim

opset15

onx_nnodes

AffinityPropagation

cluster

default

AffinityPropagation

~b-clu-64

default

name

problem

scenario

optim

opset15

ERROR-msg

AffinityPropagation

cluster

default

NO CONVERTER

AffinityPropagation

~b-clu-64

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

AffinityPropagation

cluster

default

1.0.2

1

AffinityPropagation

~b-clu-64

default

1.0.2

1

Bagging#

name

problem

scenario

optim

opset15

onx_nnodes

BaggingClassifier

b-cl

default

OK 15/1

29

BaggingClassifier

m-cl

default

OK 15/1

29

BaggingRegressor

b-reg

default

OK 15/1

22

BaggingRegressor

m-reg

default

OK 15/1

22

BaggingRegressor

~b-reg-64

default

OK 15/

22

BaggingRegressor

~m-reg-64

default

OK 15/

22

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

BaggingClassifier

b-cl

default

OK 15/1

1.0.2

11

7.1e+03

29

3

skl2onnx

1.1

1

5.9e+03

25

3

11

30

10

1

3

1

BaggingClassifier

m-cl

default

OK 15/1

1.0.2

11

1.4e+04

29

3

skl2onnx

1.1

1

1.4e+04

29

3

11

1.6e+02

10

6

3

1

BaggingRegressor

b-reg

default

OK 15/1

1.0.2

11

5.6e+04

22

1

skl2onnx

1.1

1

5.6e+04

22

1

10

1.4e+03

10

14

-1

BaggingRegressor

m-reg

default

OK 15/1

1.0.2

11

6.4e+04

22

1

skl2onnx

1.1

1

6.4e+04

22

1

10

1.4e+03

10

14

-1

BaggingRegressor

~b-reg-64

default

OK 15/

1.0.2

11

6.8e+04

22

1

skl2onnx

1.1

-1

6.8e+04

22

1

10

1.4e+03

10

14

1

BaggingRegressor

~m-reg-64

default

OK 15/

1.0.2

11

7.8e+04

22

1

skl2onnx

1.1

-1

7.8e+04

22

1

10

1.4e+03

10

14

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

BaggingClassifier

b-cl

default

OK 15/1

0.028

0.028

0.034

0.062

0.33

0.027

0.029

0.027

0.029

0.032

0.038

0.06

0.068

0.33

0.33

BaggingClassifier

m-cl

default

OK 15/1

0.028

0.028

0.035

0.085

0.52

0.027

0.029

0.027

0.029

0.034

0.038

0.083

0.087

0.51

0.54

BaggingRegressor

b-reg

default

OK 15/1

0.022

0.022

0.025

0.036

0.14

0.021

0.023

0.022

0.023

0.024

0.026

0.035

0.037

0.14

0.14

BaggingRegressor

m-reg

default

OK 15/1

0.023

0.023

0.027

0.057

0.31

0.022

0.023

0.023

0.024

0.027

0.029

0.057

0.058

0.31

0.31

BaggingRegressor

~b-reg-64

default

OK 15/

0.022

0.022

0.025

0.038

0.16

0.021

0.022

0.022

0.023

0.024

0.026

0.038

0.039

0.14

0.17

BaggingRegressor

~m-reg-64

default

OK 15/

0.022

0.023

0.027

0.057

0.31

0.022

0.023

0.023

0.024

0.027

0.028

0.056

0.059

0.3

0.31

Bayesian…#

name

problem

scenario

optim

opset15

onx_nnodes

BayesianGaussianMixture

mix

default

OK 14/

12

BayesianGaussianMixture

~mix-64

default

-1

BayesianGaussianMixture

~mix-64

default

OK 14/

12

name

problem

scenario

optim

opset15

ERROR-msg

BayesianGaussianMixture

~mix-64

default

‘<’ not supported between instances of ‘dict’ and ‘int’

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

BayesianGaussianMixture

mix

default

OK 14/

1.0.2

1

1.1e+03

12

7

skl2onnx

1.1

1.1e+03

12

7

BayesianGaussianMixture

~mix-64

default

1.0.2

1

-1

-1

-1

-1

-1

-1

BayesianGaussianMixture

~mix-64

default

OK 14/

1.0.2

1

1.2e+03

12

7

skl2onnx

1.1

1.2e+03

12

7

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

BayesianGaussianMixture

mix

default

OK 14/

0.44

0.43

0.45

0.51

0.67

0.42

0.46

0.42

0.45

0.43

0.48

0.49

0.53

0.67

0.68

BayesianGaussianMixture

~mix-64

default

OK 14/

0.43

0.43

0.44

0.55

0.88

0.41

0.45

0.41

0.45

0.42

0.48

0.52

0.57

0.88

0.89

Binarizer#

name

problem

scenario

optim

opset15

onx_nnodes

Binarizer

num-tr

default

OK 15/1

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

Binarizer

num-tr

default

OK 15/1

1.0.2

1

2e+02

1

0

skl2onnx

1.1

1

2e+02

1

0

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

Binarizer

num-tr

default

OK 15/1

0.2

0.2

0.22

0.3

0.57

0.19

0.22

0.19

0.22

0.21

0.24

0.28

0.33

0.52

0.62

Birch#

name

problem

scenario

optim

opset15

onx_nnodes

Birch

cluster

default

Birch

~b-clu-64

default

Birch

~num-tr-clu

default

Birch

~num-tr-clu-64

default

name

problem

scenario

optim

opset15

ERROR-msg

Birch

cluster

default

NO CONVERTER

Birch

~b-clu-64

default

NO CONVERTER

Birch

~num-tr-clu

default

NO CONVERTER

Birch

~num-tr-clu-64

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

Birch

cluster

default

1.0.2

1

Birch

~b-clu-64

default

1.0.2

1

Birch

~num-tr-clu

default

1.0.2

1

Birch

~num-tr-clu-64

default

1.0.2

1

Booster#

name

problem

scenario

optim

opset15

onx_nnodes

Booster

ERR: 0problem

name

problem

scenario

optim

opset15

ERROR-msg

Booster

ERR: 0problem

NO PROBLEM

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

Booster

ERR: 0problem

1.0.2

CCA#

name

problem

scenario

optim

opset15

onx_nnodes

CCA

b-reg

default

CCA

m-reg

default

CCA

num+y-tr

default

CCA

~b-reg-64

default

CCA

~m-reg-64

default

name

problem

scenario

optim

opset15

ERROR-msg

CCA

b-reg

default

NO CONVERTER

CCA

m-reg

default

NO CONVERTER

CCA

num+y-tr

default

NO CONVERTER

CCA

~b-reg-64

default

NO CONVERTER

CCA

~m-reg-64

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

CCA

b-reg

default

1.0.2

1

4

1

CCA

m-reg

default

1.0.2

1

4

1

CCA

num+y-tr

default

1.0.2

1

4

1

CCA

~b-reg-64

default

1.0.2

1

4

1

CCA

~m-reg-64

default

1.0.2

1

4

1

Calibrated#

name

problem

scenario

optim

opset15

onx_nnodes

CalibratedClassifierCV

b-cl

default

OK 15/1

53

CalibratedClassifierCV

b-cl

sgd

OK 15/1

88

CalibratedClassifierCV

m-cl

default

OK 15/1

1.5e+02

CalibratedClassifierCV

m-cl

sgd

OK 15/1

1.7e+02

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

CalibratedClassifierCV

b-cl

default

OK 15/1

1.0.2

1

4.6e+03

53

15

skl2onnx

1.1

1

4.6e+03

53

15

1

2

1

CalibratedClassifierCV

b-cl

sgd

OK 15/1

1.0.2

1

6.4e+03

88

26

skl2onnx

1.1

1

4.8e+03

68

26

6

7

1

CalibratedClassifierCV

m-cl

default

OK 15/1

1.0.2

1

1.1e+04

1.5e+02

39

skl2onnx

1.1

1

1.1e+04

1.5e+02

39

1

12

1

CalibratedClassifierCV

m-cl

sgd

OK 15/1

1.0.2

1

1.2e+04

1.7e+02

49

skl2onnx

1.1

1

1e+04

1.5e+02

49

6

17

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

CalibratedClassifierCV

b-cl

default

OK 15/1

0.37

0.37

0.38

0.5

0.85

0.36

0.38

0.37

0.38

0.37

0.4

0.49

0.51

0.85

0.85

CalibratedClassifierCV

b-cl

sgd

OK 15/1

0.63

0.64

0.67

0.96

2.2

0.56

0.66

0.63

0.65

0.65

0.68

0.95

0.97

2.2

2.2

CalibratedClassifierCV

m-cl

default

OK 15/1

0.67

0.66

0.67

0.68

0.9

0.66

0.68

0.66

0.67

0.66

0.68

0.67

0.68

0.9

0.9

CalibratedClassifierCV

m-cl

sgd

OK 15/1

0.85

0.84

0.85

0.93

1.4

0.83

0.86

0.83

0.85

0.83

0.87

0.93

0.94

1.4

1.4

ClassifierChain#

name

problem

scenario

optim

opset15

onx_nnodes

ClassifierChain

b-cl

logreg

ERR: 1training_time

ClassifierChain

m-cl

logreg

ERR: 1training_time

ClassifierChain

~b-cl-64

logreg

ERR: 1training_time

ClassifierChain

~m-label

logreg

name

problem

scenario

optim

opset15

ERROR-msg

ClassifierChain

b-cl

logreg

ERR: 1training_time

tuple index out of range

ClassifierChain

m-cl

logreg

ERR: 1training_time

tuple index out of range

ClassifierChain

~b-cl-64

logreg

ERR: 1training_time

tuple index out of range

ClassifierChain

~m-label

logreg

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

ClassifierChain

b-cl

logreg

ERR: 1training_time

1.0.2

-1

-1

-1

ClassifierChain

m-cl

logreg

ERR: 1training_time

1.0.2

-1

-1

-1

ClassifierChain

~b-cl-64

logreg

ERR: 1training_time

1.0.2

-1

-1

-1

ClassifierChain

~m-label

logreg

1.0.2

4

3

3

CountVectorizer#

name

problem

scenario

optim

opset15

onx_nnodes

CountVectorizer

text-col

default

OK 14/

6

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

CountVectorizer

text-col

default

OK 14/

1.0.2

1

1e+03

6

1

skl2onnx

1.1

1e+03

5

1

1

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

CountVectorizer

text-col

default

OK 14/

0.94

1.4

1.8

1.9

2

0.9

0.97

1.3

1.4

1.8

1.9

1.9

1.9

2

2

DictVectorizer#

name

problem

scenario

optim

opset15

onx_nnodes

DictVectorizer

key-int-col

default

name

problem

scenario

optim

opset15

ERROR-msg

DictVectorizer

key-int-col

default

Unsupported data_type ‘DictionaryType(key_type=StringTensorType(shape=[1]),…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

DictVectorizer

key-int-col

default

1.0.2

1

DictionaryLearning#

name

problem

scenario

optim

opset15

onx_nnodes

DictionaryLearning

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

DictionaryLearning

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

DictionaryLearning

num-tr

default

1.0.2

1

EllipticEnvelope#

name

problem

scenario

optim

opset15

onx_nnodes

EllipticEnvelope

outlier

default

name

problem

scenario

optim

opset15

ERROR-msg

EllipticEnvelope

outlier

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

EllipticEnvelope

outlier

default

1.0.2

1

FactorAnalysis#

name

problem

scenario

optim

opset15

onx_nnodes

FactorAnalysis

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

FactorAnalysis

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

FactorAnalysis

num-tr

default

1.0.2

1

FastICA#

name

problem

scenario

optim

opset15

onx_nnodes

FastICA

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

FastICA

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

FastICA

num-tr

default

1.0.2

1

Feature…#

name

problem

scenario

optim

opset15

onx_nnodes

FeatureHasher

key-str-col

default

name

problem

scenario

optim

opset15

ERROR-msg

FeatureHasher

key-str-col

default

Unsupported data_type ‘DictionaryType(key_type=StringTensorType(shape=[1]),…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

FeatureHasher

key-str-col

default

1.0.2

1

FunctionTransformer#

name

problem

scenario

optim

opset15

onx_nnodes

FunctionTransformer

num-tr

default

OK 14/

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

FunctionTransformer

num-tr

default

OK 14/

1.0.2

1

1.6e+02

1

0

skl2onnx

1.1

1.6e+02

1

0

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

FunctionTransformer

num-tr

default

OK 14/

4.1

4.1

3.6

4.3

6.5

2.3

4.9

3.3

4.8

1.5

5.3

3.7

4.7

5

8.3

Gamma#

name

problem

scenario

optim

opset15

onx_nnodes

GammaRegressor

b-reg

default

ERR: 1training_time

GammaRegressor

m-reg

default

ERR: 1training_time

GammaRegressor

~b-reg-64

default

ERR: 1training_time

GammaRegressor

~m-reg-64

default

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

GammaRegressor

b-reg

default

ERR: 1training_time

Some value(s) of y are out of the valid range for family GammaDistribution

GammaRegressor

m-reg

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

GammaRegressor

~b-reg-64

default

ERR: 1training_time

Some value(s) of y are out of the valid range for family GammaDistribution

GammaRegressor

~m-reg-64

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

GammaRegressor

b-reg

default

ERR: 1training_time

1.0.2

GammaRegressor

m-reg

default

ERR: 1training_time

1.0.2

GammaRegressor

~b-reg-64

default

ERR: 1training_time

1.0.2

GammaRegressor

~m-reg-64

default

ERR: 1training_time

1.0.2

GaussianMixture#

name

problem

scenario

optim

opset15

onx_nnodes

GaussianMixture

mix

default

OK 14/

11

GaussianMixture

~mix-64

default

-1

GaussianMixture

~mix-64

default

OK 14/

11

name

problem

scenario

optim

opset15

ERROR-msg

GaussianMixture

~mix-64

default

‘<’ not supported between instances of ‘dict’ and ‘int’

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

GaussianMixture

mix

default

OK 14/

1.0.2

1

9.9e+02

11

6

skl2onnx

1.1

9.9e+02

11

6

GaussianMixture

~mix-64

default

1.0.2

1

-1

-1

-1

-1

-1

-1

GaussianMixture

~mix-64

default

OK 14/

1.0.2

1

1.1e+03

11

6

skl2onnx

1.1

1.1e+03

11

6

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

GaussianMixture

mix

default

OK 14/

0.62

0.62

0.63

0.66

0.74

0.6

0.64

0.6

0.64

0.59

0.68

0.63

0.69

0.73

0.75

GaussianMixture

~mix-64

default

OK 14/

0.62

0.61

0.62

0.72

0.98

0.6

0.66

0.59

0.65

0.59

0.67

0.68

0.76

0.97

0.98

GaussianProcess#

name

problem

scenario

optim

opset15

onx_nnodes

GaussianProcessClassifier

b-cl

dotproduct

cdist

e<0.001 15/1

43

GaussianProcessClassifier

b-cl

dotproduct

cdist

e<0.001 15/1

43

GaussianProcessClassifier

b-cl

expsine

ERR: 1training_time

-1

GaussianProcessClassifier

b-cl

rational

cdist

e<0.001 15/1

46

GaussianProcessClassifier

b-cl

rational

cdist

e<0.001 15/1

46

GaussianProcessClassifier

b-cl

rbf

cdist

e<0.001 15/1

57

GaussianProcessClassifier

b-cl

rbf

cdist

e<0.001 15/1

57

GaussianProcessClassifier

m-cl

dotproduct

-1

GaussianProcessClassifier

m-cl

expsine

ERR: 1training_time

-1

GaussianProcessClassifier

m-cl

rational

-1

GaussianProcessClassifier

m-cl

rbf

-1

GaussianProcessClassifier

~b-cl-64

dotproduct

cdist

OK 15/1

43

GaussianProcessClassifier

~b-cl-64

dotproduct

cdist

OK 15/1

43

GaussianProcessClassifier

~b-cl-64

expsine

ERR: 1training_time

-1

GaussianProcessClassifier

~b-cl-64

rational

cdist

OK 15/1

46

GaussianProcessClassifier

~b-cl-64

rational

cdist

OK 15/1

46

GaussianProcessClassifier

~b-cl-64

rbf

cdist

OK 15/1

57

GaussianProcessRegressor

b-reg

dotproduct

OK 15/

5

GaussianProcessRegressor

b-reg

dotproduct

cdist

OK 15/

5

GaussianProcessRegressor

b-reg

expsine

cdist

OK 15/

11

GaussianProcessRegressor

b-reg

rational

cdist

OK 15/

7

GaussianProcessRegressor

b-reg

rbf

cdist

OK 15/

18

GaussianProcessRegressor

b-reg

rbf

cdist

OK 15/

18

GaussianProcessRegressor

~b-reg-64

dotproduct

OK 15/

5

GaussianProcessRegressor

~b-reg-64

dotproduct

cdist

OK 15/

5

GaussianProcessRegressor

~b-reg-64

expsine

cdist

OK 15/

11

GaussianProcessRegressor

~b-reg-64

rational

cdist

OK 15/

7

GaussianProcessRegressor

~b-reg-64

rbf

cdist

OK 15/

18

GaussianProcessRegressor

~b-reg-NF-64

dotproduct

OK 15/

3

GaussianProcessRegressor

~b-reg-NF-64

dotproduct

cdist

OK 15/

3

GaussianProcessRegressor

~b-reg-NF-64

expsine

cdist

OK 15/

3

GaussianProcessRegressor

~b-reg-NF-64

rational

cdist

OK 15/

3

GaussianProcessRegressor

~b-reg-NF-64

rbf

cdist

OK 15/

3

GaussianProcessRegressor

~b-reg-NF-cov-64

dotproduct

OK 15/

7

GaussianProcessRegressor

~b-reg-NF-cov-64

dotproduct

cdist

OK 15/

7

GaussianProcessRegressor

~b-reg-NF-cov-64

expsine

cdist

OK 15/

18

GaussianProcessRegressor

~b-reg-NF-cov-64

rational

cdist

OK 15/

13

GaussianProcessRegressor

~b-reg-NF-cov-64

rbf

cdist

OK 15/

20

GaussianProcessRegressor

~b-reg-NF-cov-64

rbf

cdist

OK 15/

20

GaussianProcessRegressor

~b-reg-NF-std-64

dotproduct

OK 15/

7

GaussianProcessRegressor

~b-reg-NF-std-64

dotproduct

cdist

OK 15/

7

GaussianProcessRegressor

~b-reg-NF-std-64

expsine

cdist

OK 15/

8

GaussianProcessRegressor

~b-reg-NF-std-64

expsine

cdist

OK 15/

8

GaussianProcessRegressor

~b-reg-NF-std-64

rational

cdist

OK 15/

8

GaussianProcessRegressor

~b-reg-NF-std-64

rbf

cdist

OK 15/

8

GaussianProcessRegressor

~b-reg-NF-std-64

rbf

cdist

OK 15/

8

GaussianProcessRegressor

~b-reg-NSV-64

dotproduct

OK 15/

5

GaussianProcessRegressor

~b-reg-NSV-64

dotproduct

cdist

OK 15/

5

GaussianProcessRegressor

~b-reg-NSV-64

expsine

cdist

OK 15/

11

GaussianProcessRegressor

~b-reg-NSV-64

rational

cdist

OK 15/

7

GaussianProcessRegressor

~b-reg-NSV-64

rbf

cdist

OK 15/

18

GaussianProcessRegressor

~b-reg-cov-64

dotproduct

-1

GaussianProcessRegressor

~b-reg-cov-64

dotproduct

-1

GaussianProcessRegressor

~b-reg-cov-64

expsine

-1

GaussianProcessRegressor

~b-reg-cov-64

rational

-1

GaussianProcessRegressor

~b-reg-cov-64

rbf

-1

GaussianProcessRegressor

~b-reg-std-NSV-64

dotproduct

OK 15/

14

GaussianProcessRegressor

~b-reg-std-NSV-64

dotproduct

cdist

OK 15/

14

GaussianProcessRegressor

~b-reg-std-NSV-64

expsine

cdist

OK 15/

21

GaussianProcessRegressor

~b-reg-std-NSV-64

rational

cdist

OK 15/

17

GaussianProcessRegressor

~b-reg-std-NSV-64

rbf

cdist

OK 15/

28

GaussianProcessRegressor

~b-reg-std-NSV-64

rbf

cdist

OK 15/

28

name

problem

scenario

optim

opset15

ERROR-msg

GaussianProcessClassifier

b-cl

expsine

ERR: 1training_time

35-th leading minor of the array is not positive definite

GaussianProcessClassifier

m-cl

dotproduct

Only binary classification is iplemented.

GaussianProcessClassifier

m-cl

expsine

ERR: 1training_time

35-th leading minor of the array is not positive definite

GaussianProcessClassifier

m-cl

rational

Only binary classification is iplemented.

GaussianProcessClassifier

m-cl

rbf

Only binary classification is iplemented.

GaussianProcessClassifier

~b-cl-64

expsine

ERR: 1training_time

35-th leading minor of the array is not positive definite

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

GaussianProcessClassifier

b-cl

dotproduct

cdist

e<0.001 15/1

1.0.2

1

5.6e+04

43

17

skl2onnx

1.1

1

5.6e+04

42

17

2

2

1

1

GaussianProcessClassifier

b-cl

dotproduct

cdist

e<0.001 15/1

1.0.2

1

5.6e+04

43

17

skl2onnx

1.1

1

5.6e+04

42

17

2

2

1

1

GaussianProcessClassifier

b-cl

expsine

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessClassifier

b-cl

rational

cdist

e<0.001 15/1

1.0.2

1

5.7e+04

46

18

skl2onnx

1.1

1

5.7e+04

45

18

2

2

1

1

GaussianProcessClassifier

b-cl

rational

cdist

e<0.001 15/1

1.0.2

1

5.7e+04

46

18

skl2onnx

1.1

1

5.7e+04

45

18

2

2

1

1

GaussianProcessClassifier

b-cl

rbf

cdist

e<0.001 15/1

1.0.2

1

5.7e+04

57

16

skl2onnx

1.1

1

5.7e+04

52

16

2

2

1

1

GaussianProcessClassifier

b-cl

rbf

cdist

e<0.001 15/1

1.0.2

1

5.7e+04

57

16

skl2onnx

1.1

1

5.7e+04

52

16

2

2

1

1

GaussianProcessClassifier

m-cl

dotproduct

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessClassifier

m-cl

expsine

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessClassifier

m-cl

rational

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessClassifier

m-cl

rbf

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessClassifier

~b-cl-64

dotproduct

cdist

OK 15/1

1.0.2

1

1.1e+05

43

17

skl2onnx

1.1

1

1.1e+05

42

17

2

2

1

1

GaussianProcessClassifier

~b-cl-64

dotproduct

cdist

OK 15/1

1.0.2

1

1.1e+05

43

17

skl2onnx

1.1

1

1.1e+05

42

17

2

2

1

1

GaussianProcessClassifier

~b-cl-64

expsine

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessClassifier

~b-cl-64

rational

cdist

OK 15/1

1.0.2

1

1.1e+05

46

18

skl2onnx

1.1

1

1.1e+05

45

18

2

2

1

1

GaussianProcessClassifier

~b-cl-64

rational

cdist

OK 15/1

1.0.2

1

1.1e+05

46

18

skl2onnx

1.1

1

1.1e+05

45

18

2

2

1

1

GaussianProcessClassifier

~b-cl-64

rbf

cdist

OK 15/1

1.0.2

1

1.1e+05

57

16

skl2onnx

1.1

1

1.1e+05

52

16

2

2

1

1

GaussianProcessRegressor

b-reg

dotproduct

OK 15/

1.0.2

1

2.8e+03

5

5

skl2onnx

1.1

2.8e+03

5

5

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

b-reg

dotproduct

cdist

OK 15/

1.0.2

1

2.8e+03

5

5

skl2onnx

1.1

2.8e+03

5

5

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

b-reg

expsine

cdist

OK 15/

1.0.2

1

3.2e+03

11

9

skl2onnx

1.1

3.2e+03

11

9

1

1

-1

-1

-1

-1

GaussianProcessRegressor

b-reg

rational

cdist

OK 15/

1.0.2

1

3e+03

7

7

skl2onnx

1.1

3e+03

7

7

1

1

-1

-1

-1

-1

GaussianProcessRegressor

b-reg

rbf

cdist

OK 15/

1.0.2

1

3.7e+03

18

6

skl2onnx

1.1

3.6e+03

16

6

1

1

-1

-1

-1

-1

GaussianProcessRegressor

b-reg

rbf

cdist

OK 15/

1.0.2

1

3.7e+03

18

6

skl2onnx

1.1

3.6e+03

16

6

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-64

dotproduct

OK 15/

1.0.2

1

5e+03

5

5

skl2onnx

1.1

5e+03

5

5

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-64

dotproduct

cdist

OK 15/

1.0.2

1

5e+03

5

5

skl2onnx

1.1

5e+03

5

5

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-64

expsine

cdist

OK 15/

1.0.2

1

5.5e+03

11

9

skl2onnx

1.1

5.5e+03

11

9

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-64

rational

cdist

OK 15/

1.0.2

1

5.2e+03

7

7

skl2onnx

1.1

5.2e+03

7

7

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-64

rbf

cdist

OK 15/

1.0.2

1

6.1e+03

18

6

skl2onnx

1.1

5.9e+03

16

6

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-64

dotproduct

OK 15/

1.0.2

-1

3.6e+02

3

1

skl2onnx

1.1

3.6e+02

3

1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-64

dotproduct

cdist

OK 15/

1.0.2

-1

3.6e+02

3

1

skl2onnx

1.1

3.6e+02

3

1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-64

expsine

cdist

OK 15/

1.0.2

-1

3.6e+02

3

1

skl2onnx

1.1

3.6e+02

3

1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-64

rational

cdist

OK 15/

1.0.2

-1

3.6e+02

3

1

skl2onnx

1.1

3.6e+02

3

1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-64

rbf

cdist

OK 15/

1.0.2

-1

3.6e+02

3

1

skl2onnx

1.1

3.6e+02

3

1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-cov-64

dotproduct

OK 15/

1.0.2

-1

6e+02

7

2

skl2onnx

1.1

5.6e+02

6

2

-1

-1

1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-cov-64

dotproduct

cdist

OK 15/

1.0.2

-1

6e+02

7

2

skl2onnx

1.1

5.6e+02

6

2

-1

-1

1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-cov-64

expsine

cdist

OK 15/

1.0.2

-1

1.4e+03

18

5

skl2onnx

1.1

1.3e+03

16

5

-1

-1

3

1

1

1

GaussianProcessRegressor

~b-reg-NF-cov-64

rational

cdist

OK 15/

1.0.2

-1

1.2e+03

13

4

skl2onnx

1.1

1.1e+03

11

4

-1

-1

3

1

1

1

GaussianProcessRegressor

~b-reg-NF-cov-64

rbf

cdist

OK 15/

1.0.2

-1

1.7e+03

20

2

skl2onnx

1.1

1.3e+03

15

2

-1

-1

1

1

1

1

GaussianProcessRegressor

~b-reg-NF-cov-64

rbf

cdist

OK 15/

1.0.2

-1

1.7e+03

20

2

skl2onnx

1.1

1.3e+03

15

2

-1

-1

1

1

1

1

GaussianProcessRegressor

~b-reg-NF-std-64

dotproduct

OK 15/

1.0.2

-1

6.3e+02

7

2

skl2onnx

1.1

6.3e+02

7

2

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-std-64

dotproduct

cdist

OK 15/

1.0.2

-1

6.3e+02

7

2

skl2onnx

1.1

6.3e+02

7

2

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-std-64

expsine

cdist

OK 15/

1.0.2

-1

7.1e+02

8

2

skl2onnx

1.1

5.8e+02

6

2

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-std-64

expsine

cdist

OK 15/

1.0.2

-1

7.1e+02

8

2

skl2onnx

1.1

5.9e+02

6

2

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-std-64

rational

cdist

OK 15/

1.0.2

-1

7.1e+02

8

2

skl2onnx

1.1

5.8e+02

6

2

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-std-64

rbf

cdist

OK 15/

1.0.2

-1

7.1e+02

8

2

skl2onnx

1.1

5.8e+02

6

2

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NF-std-64

rbf

cdist

OK 15/

1.0.2

-1

7.1e+02

8

2

skl2onnx

1.1

5.9e+02

6

2

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NSV-64

dotproduct

OK 15/

1.0.2

1

5e+03

5

5

skl2onnx

1.1

5e+03

5

5

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NSV-64

dotproduct

cdist

OK 15/

1.0.2

1

5e+03

5

5

skl2onnx

1.1

5e+03

5

5

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NSV-64

expsine

cdist

OK 15/

1.0.2

1

5.5e+03

11

9

skl2onnx

1.1

5.5e+03

11

9

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NSV-64

rational

cdist

OK 15/

1.0.2

1

5.2e+03

7

7

skl2onnx

1.1

5.2e+03

7

7

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-NSV-64

rbf

cdist

OK 15/

1.0.2

1

6.1e+03

18

6

skl2onnx

1.1

5.9e+03

16

6

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-cov-64

dotproduct

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-cov-64

dotproduct

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-cov-64

expsine

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-cov-64

rational

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-cov-64

rbf

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-std-NSV-64

dotproduct

OK 15/

1.0.2

1

1.1e+05

14

8

skl2onnx

1.1

1.1e+05

14

8

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-std-NSV-64

dotproduct

cdist

OK 15/

1.0.2

1

1.1e+05

14

8

skl2onnx

1.1

1.1e+05

14

8

1

-1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-std-NSV-64

expsine

cdist

OK 15/

1.0.2

1

1.1e+05

21

13

skl2onnx

1.1

1.1e+05

21

13

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-std-NSV-64

rational

cdist

OK 15/

1.0.2

1

1.1e+05

17

10

skl2onnx

1.1

1.1e+05

17

10

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-std-NSV-64

rbf

cdist

OK 15/

1.0.2

1

1.1e+05

28

9

skl2onnx

1.1

1.1e+05

24

9

1

1

-1

-1

-1

-1

GaussianProcessRegressor

~b-reg-std-NSV-64

rbf

cdist

OK 15/

1.0.2

1

1.1e+05

28

9

skl2onnx

1.1

1.1e+05

24

9

1

1

-1

-1

-1

-1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

GaussianProcessClassifier

b-cl

dotproduct

cdist

e<0.001 15/1

1.1

1.1

1

0.43

0.49

0.7

1.2

0.62

1.2

0.98

1

0.18

0.95

0.45

0.53

GaussianProcessClassifier

b-cl

dotproduct

cdist

e<0.001 15/1

1.1

1.1

0.99

0.45

0.38

0.7

1.2

0.61

1.2

0.96

1

0.18

1.1

0.34

0.41

GaussianProcessClassifier

b-cl

rational

cdist

e<0.001 15/1

1.1

1.1

0.38

0.46

0.52

0.57

1.2

0.93

1.2

0.26

0.42

0.26

0.56

0.5

0.53

GaussianProcessClassifier

b-cl

rational

cdist

e<0.001 15/1

1.1

1.1

0.66

0.33

0.54

0.57

1.2

0.93

1.4

0.26

0.85

0.24

0.46

0.5

0.57

GaussianProcessClassifier

b-cl

rbf

cdist

e<0.001 15/1

1.3

1.2

1

0.68

0.61

0.84

1.4

0.61

1.4

0.94

1.1

0.44

1.1

0.58

0.65

GaussianProcessClassifier

b-cl

rbf

cdist

e<0.001 15/1

1.3

1.3

1

0.59

0.57

0.84

1.4

0.61

2.4

0.95

1

0.44

0.7

0.51

0.62

GaussianProcessClassifier

~b-cl-64

dotproduct

cdist

OK 15/1

1.2

1.3

3

0.94

0.87

0.43

1.5

0.69

1.4

1.2

10

0.24

4

0.68

1.2

GaussianProcessClassifier

~b-cl-64

dotproduct

cdist

OK 15/1

1.2

1.3

3.4

0.76

1.2

0.43

1.4

0.69

2.2

1.2

14

0.25

2.1

0.93

1.6

GaussianProcessClassifier

~b-cl-64

rational

cdist

OK 15/1

1.3

1.3

1.3

0.81

1.2

0.83

1.3

1.1

1.3

0.99

2

0.51

1.6

1.1

1.3

GaussianProcessClassifier

~b-cl-64

rational

cdist

OK 15/1

1.3

1.3

1.2

0.73

1

0.84

1.4

1.2

2.1

1

1.8

0.51

1.2

0.94

1.1

GaussianProcessClassifier

~b-cl-64

rbf

cdist

OK 15/1

1.3

1.5

1.3

2.7

0.97

0.47

1.5

1.4

1.5

1.2

1.3

0.7

5.7

0.93

1

GaussianProcessRegressor

b-reg

dotproduct

OK 15/

0.56

0.5

0.46

0.46

0.52

0.53

0.58

0.4

0.53

0.42

0.5

0.46

0.48

0.52

0.52

GaussianProcessRegressor

b-reg

expsine

cdist

OK 15/

0.84

0.75

0.69

0.67

0.94

0.78

0.87

0.67

0.78

0.25

0.87

0.52

0.9

0.94

0.95

GaussianProcessRegressor

b-reg

rational

cdist

OK 15/

0.6

0.5

0.46

0.4

0.49

0.57

0.63

0.48

0.52

0.45

0.47

0.35

0.47

0.49

0.49

GaussianProcessRegressor

b-reg

rbf

cdist

OK 15/

1.4

1.1

0.38

0.6

0.55

1.3

1.4

0.91

1.1

0.35

0.43

0.59

0.62

0.51

0.59

GaussianProcessRegressor

b-reg

rbf

cdist

OK 15/

1.4

1.1

0.38

0.6

0.55

1.3

1.4

0.92

1.1

0.35

0.4

0.59

0.62

0.51

0.59

GaussianProcessRegressor

~b-reg-64

dotproduct

OK 15/

0.55

0.45

0.22

0.23

0.29

0.52

0.56

0.37

0.48

0.21

0.25

0.23

0.23

0.29

0.29

GaussianProcessRegressor

~b-reg-64

expsine

cdist

OK 15/

0.84

0.74

1.1

1

1.2

0.81

0.88

0.22

0.87

1.1

1.1

0.85

1.2

1.2

1.2

GaussianProcessRegressor

~b-reg-64

rational

cdist

OK 15/

0.62

0.64

0.87

0.9

0.96

0.59

0.65

0.6

0.67

0.83

0.89

0.79

1.1

0.96

0.97

GaussianProcessRegressor

~b-reg-64

rbf

cdist

OK 15/

1.4

1.1

1

0.51

0.84

1.3

1.5

0.77

1.2

0.99

1

0.47

0.68

0.77

0.91

GaussianProcessRegressor

~b-reg-NF-64

dotproduct

OK 15/

0.98

1

1.1

1.3

4

0.95

1

0.94

1.1

1

1.1

1.2

1.4

3.6

4.5

GaussianProcessRegressor

~b-reg-NF-64

expsine

cdist

OK 15/

1

1

1.1

1.3

4.1

0.96

1

0.96

1.1

0.92

1.2

1.3

1.4

3.7

4.6

GaussianProcessRegressor

~b-reg-NF-64

rational

cdist

OK 15/

0.98

1

1.1

1.3

3.8

0.93

1

0.96

1.1

0.99

1.2

1.3

1.4

3.3

4.4

GaussianProcessRegressor

~b-reg-NF-64

rbf

cdist

OK 15/

0.98

1

1.1

1.3

4

0.95

1

0.97

1.2

0.96

1.1

1.2

1.4

3.7

4.5

GaussianProcessRegressor

~b-reg-NF-cov-64

dotproduct

OK 15/

1.2

1.2

1.2

1.9

1.1

1.2

1.1

1.2

1.1

1.4

1.8

2

GaussianProcessRegressor

~b-reg-NF-cov-64

expsine

cdist

OK 15/

2.2

6.5

8

2.4

2.2

2.3

6

6.9

8

8.1

2.3

2.4

GaussianProcessRegressor

~b-reg-NF-cov-64

rational

cdist

OK 15/

1.7

6.1

21

5.2

1.6

1.8

5.8

6.2

20

21

5.2

5.3

GaussianProcessRegressor

~b-reg-NF-cov-64

rbf

cdist

OK 15/

2.6

6.5

22

5.7

2.5

2.7

5.8

6.8

21

23

5.7

5.8

GaussianProcessRegressor

~b-reg-NF-cov-64

rbf

cdist

OK 15/

2.6

6.5

22

5.8

2.5

2.7

5.8

6.7

21

23

5.8

5.8

GaussianProcessRegressor

~b-reg-NF-std-64

dotproduct

OK 15/

1.3

1.3

1.4

1.5

2.1

1.3

1.4

1.3

1.4

1.3

1.5

1.4

1.6

2

2.1

GaussianProcessRegressor

~b-reg-NF-std-64

expsine

cdist

OK 15/

1.6

1.6

1.7

2

3.7

1.5

1.6

1.6

1.7

1.6

1.8

1.8

2.1

3.4

4

GaussianProcessRegressor

~b-reg-NF-std-64

expsine

cdist

OK 15/

1.6

1.6

1.7

2

3.7

1.5

1.6

1.5

1.7

1.6

1.8

1.8

2.2

3.4

4

GaussianProcessRegressor

~b-reg-NF-std-64

rational

cdist

OK 15/

1.6

1.6

1.7

2

3.8

1.5

1.6

1.5

1.7

1.6

1.8

1.9

2.2

3.5

4.1

GaussianProcessRegressor

~b-reg-NF-std-64

rbf

cdist

OK 15/

1.6

1.6

1.7

2

3.7

1.5

1.6

1.5

1.6

1.6

1.8

1.9

2.2

3.7

3.7

GaussianProcessRegressor

~b-reg-NF-std-64

rbf

cdist

OK 15/

1.6

1.6

1.7

2

3.8

1.5

1.6

1.5

1.7

1.6

1.8

1.9

2.1

3.6

4

GaussianProcessRegressor

~b-reg-NSV-64

dotproduct

OK 15/

0.53

0.45

0.21

0.45

0.31

0.4

0.57

0.28

0.48

0.18

0.25

0.41

0.51

0.28

0.35

GaussianProcessRegressor

~b-reg-NSV-64

expsine

cdist

OK 15/

0.85

0.75

0.56

0.59

1.2

0.76

0.89

0.24

0.91

0.54

0.57

0.57

0.6

1.2

1.2

GaussianProcessRegressor

~b-reg-NSV-64

rational

cdist

OK 15/

0.64

0.65

0.88

0.87

0.97

0.6

0.66

0.62

0.66

0.86

0.89

0.75

0.94

0.96

0.97

GaussianProcessRegressor

~b-reg-NSV-64

rbf

cdist

OK 15/

1.4

1.2

1.3

0.72

0.78

1.4

1.5

1.1

1.2

0.99

3.7

0.47

0.94

0.75

0.82

GaussianProcessRegressor

~b-reg-std-NSV-64

dotproduct

OK 15/

0.65

0.92

0.38

0.7

1.2

0.3

0.86

0.89

0.97

0.14

0.51

0.61

0.97

1

1.6

GaussianProcessRegressor

~b-reg-std-NSV-64

expsine

cdist

OK 15/

0.95

1.2

1.4

1.2

1.4

0.84

1

1

1.2

1.2

3.2

1

1.3

1.4

1.5

GaussianProcessRegressor

~b-reg-std-NSV-64

rational

cdist

OK 15/

0.81

1

1.1

0.94

1.1

0.78

0.86

0.97

1

1

1.1

0.81

1.1

1.1

1.1

GaussianProcessRegressor

~b-reg-std-NSV-64

rbf

cdist

OK 15/

1.3

1.4

1.2

0.79

1.1

1.2

1.3

1.2

1.4

1.2

1.2

0.6

1.2

1.1

1.1

GaussianProcessRegressor

~b-reg-std-NSV-64

rbf

cdist

OK 15/

1.3

1.4

1.2

0.79

1.1

1.2

1.3

1.1

1.4

1.2

1.3

0.6

1.2

1.1

1.1

GaussianRandomProjection#

name

problem

scenario

optim

opset15

onx_nnodes

GaussianRandomProjection

num-tr

eps95

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

GaussianRandomProjection

num-tr

eps95

ERR: 1training_time

eps=0.950000 and n_samples=112 lead to a target dimension of 114 which is l…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

GaussianRandomProjection

num-tr

eps95

ERR: 1training_time

1.0.2

GenericUnivariateSelect#

name

problem

scenario

optim

opset15

onx_nnodes

GenericUnivariateSelect

num+y-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

GenericUnivariateSelect

num+y-tr

default

Model ‘GenericUnivariateSelect’ did not select any feature. This model cann…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

GenericUnivariateSelect

num+y-tr

default

1.0.2

1

GradientBoosting#

name

problem

scenario

optim

opset15

onx_nnodes

GradientBoostingClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1

GradientBoostingClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1

GradientBoostingRegressor

b-reg

default

OK 15/1

1

GradientBoostingRegressor

~b-reg-64

default

OK 15/

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

GradientBoostingClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

2e+02

2.2e+04

1

0

skl2onnx

1.1

1

2.2e+04

1

0

5.5e+02

2e+02

3

GradientBoostingClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

2e+02

3.1e+05

1

0

skl2onnx

1.1

1

3.1e+05

1

0

2.9e+03

2e+02

3

GradientBoostingRegressor

b-reg

default

OK 15/1

1.0.2

2e+02

1e+05

1

0

skl2onnx

1.1

1

1e+05

1

0

2.8e+03

2e+02

3

-1

GradientBoostingRegressor

~b-reg-64

default

OK 15/

1.0.2

2e+02

1.2e+05

1

0

skl2onnx

1.1

-1

1.2e+05

1

0

2.8e+03

2e+02

3

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

GradientBoostingClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.073

0.099

0.15

0.26

0.31

0.071

0.076

0.09

0.18

0.15

0.16

0.26

0.27

0.31

0.31

GradientBoostingClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.041

0.079

0.14

0.2

0.21

0.041

0.043

0.078

0.082

0.14

0.14

0.2

0.2

0.21

0.21

GradientBoostingRegressor

b-reg

default

OK 15/1

0.078

0.24

0.97

1.6

1.8

0.073

0.085

0.2

0.26

0.93

1.1

1.6

1.6

1.8

1.8

GradientBoostingRegressor

~b-reg-64

default

OK 15/

0.079

0.24

0.56

0.88

0.97

0.075

0.086

0.23

0.24

0.54

0.57

0.88

0.88

0.96

0.97

GridSearch#

name

problem

scenario

optim

opset15

onx_nnodes

GridSearchCV

b-cl

cl

{‘zipmap’: False}

OK 14/1

4

GridSearchCV

b-reg

reg

OK 14/1

2

GridSearchCV

cluster

reg

OK 14/

9

GridSearchCV

m-cl

cl

{‘zipmap’: False}

OK 14/1

4

GridSearchCV

m-reg

reg

OK 14/1

2

GridSearchCV

~b-cl-64

cl

{‘zipmap’: False}

OK 14/1

13

GridSearchCV

~b-reg-64

reg

-1

name

problem

scenario

optim

opset15

ERROR-msg

GridSearchCV

~b-reg-64

reg

‘float’ object has no attribute ‘reshape’

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

GridSearchCV

b-cl

cl

{‘zipmap’: False}

OK 14/1

1.0.2

1

5.8e+02

4

0

skl2onnx

1.1

1

4.9e+02

2

0

-1

-1

2

GridSearchCV

b-reg

reg

OK 14/1

1.0.2

1

3e+02

2

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

-1

1

GridSearchCV

cluster

reg

OK 14/

1.0.2

1

7.4e+02

9

3

skl2onnx

1.1

-1

6.6e+02

7

3

-1

-1

2

GridSearchCV

m-cl

cl

{‘zipmap’: False}

OK 14/1

1.0.2

1

6.1e+02

4

0

skl2onnx

1.1

1

5.2e+02

2

0

-1

-1

2

GridSearchCV

m-reg

reg

OK 14/1

1.0.2

1

3.4e+02

2

0

skl2onnx

1.1

1

3e+02

1

0

-1

-1

1

GridSearchCV

~b-cl-64

cl

{‘zipmap’: False}

OK 14/1

1.0.2

1

1.1e+03

13

5

skl2onnx

1.1

1

1e+03

11

5

1

2

2

GridSearchCV

~b-reg-64

reg

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

GridSearchCV

b-cl

cl

{‘zipmap’: False}

OK 14/1

0.46

0.49

0.52

0.84

1.2

0.44

0.47

0.46

0.52

0.48

0.56

0.79

0.89

1

1.6

GridSearchCV

b-reg

reg

OK 14/1

0.27

0.27

0.27

0.32

0.4

0.26

0.28

0.26

0.29

0.25

0.3

0.29

0.36

0.34

0.49

GridSearchCV

cluster

reg

OK 14/

0.24

0.26

0.28

0.093

1.1

0.24

0.25

0.25

0.27

0.27

0.31

0.059

0.12

1.1

1.2

GridSearchCV

m-cl

cl

{‘zipmap’: False}

OK 14/1

0.49

0.5

0.52

0.58

0.63

0.47

0.51

0.48

0.53

0.48

0.56

0.55

0.6

0.63

0.63

GridSearchCV

m-reg

reg

OK 14/1

0.27

0.28

0.3

0.43

0.73

0.26

0.29

0.26

0.31

0.27

0.36

0.4

0.45

0.68

0.79

GridSearchCV

~b-cl-64

cl

{‘zipmap’: False}

OK 14/1

1.3

1.4

1.5

2.5

5.1

1.2

1.3

1.3

1.5

1.4

1.6

2.3

2.7

5.1

5.2

HashingVectorizer#

name

problem

scenario

optim

opset15

onx_nnodes

HashingVectorizer

num-tr

default

ERR: 3prediction

name

problem

scenario

optim

opset15

ERROR-msg

HashingVectorizer

num-tr

default

ERR: 3prediction

‘numpy.ndarray’ object has no attribute ‘lower’

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

HashingVectorizer

num-tr

default

ERR: 3prediction

1.0.2

1

HistGradientBoosting#

name

problem

scenario

optim

opset15

onx_nnodes

HistGradientBoostingClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1

HistGradientBoostingClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1

HistGradientBoostingClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1

HistGradientBoostingClassifier

~b-cl-nan

default

{‘zipmap’: False}

OK 15/1

1

HistGradientBoostingRegressor

b-reg

default

OK 15/1

1

HistGradientBoostingRegressor

~b-reg-64

default

OK 15/

1

HistGradientBoostingRegressor

~b-reg-nan

default

OK 15/1

1

HistGradientBoostingRegressor

~b-reg-nan-64

default

OK 15/

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

HistGradientBoostingClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1.2e+04

1

0

skl2onnx

1.1

1

1.2e+04

1

0

-1

HistGradientBoostingClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

7.6e+04

1

0

skl2onnx

1.1

1

7.6e+04

1

0

-1

HistGradientBoostingClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1.0.2

1

1.2e+04

1

0

skl2onnx

1.1

-1

1.2e+04

1

0

1

HistGradientBoostingClassifier

~b-cl-nan

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

3e+04

1

0

skl2onnx

1.1

1

3e+04

1

0

-1

HistGradientBoostingRegressor

b-reg

default

OK 15/1

1.0.2

1

2.7e+04

1

0

skl2onnx

1.1

1

2.7e+04

1

0

-1

HistGradientBoostingRegressor

~b-reg-64

default

OK 15/

1.0.2

1

3.3e+04

1

0

skl2onnx

1.1

-1

3.3e+04

1

0

1

HistGradientBoostingRegressor

~b-reg-nan

default

OK 15/1

1.0.2

1

3e+04

1

0

skl2onnx

1.1

1

3e+04

1

0

-1

HistGradientBoostingRegressor

~b-reg-nan-64

default

OK 15/

1.0.2

1

3.5e+04

1

0

skl2onnx

1.1

-1

3.5e+04

1

0

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

HistGradientBoostingClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.0064

0.0085

0.016

0.072

0.25

0.0056

0.0068

0.0063

0.01

0.015

0.016

0.07

0.074

0.25

0.25

HistGradientBoostingClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.0027

0.0044

0.013

0.072

0.23

0.0026

0.0029

0.0039

0.0047

0.012

0.013

0.062

0.082

0.23

0.23

HistGradientBoostingClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

0.021

0.0084

0.016

0.07

0.25

0.0063

0.3

0.0068

0.009

0.015

0.017

0.068

0.072

0.25

0.25

HistGradientBoostingClassifier

~b-cl-nan

default

{‘zipmap’: False}

OK 15/1

0.0065

0.0085

0.016

0.079

0.22

0.0062

0.0072

0.0068

0.009

0.011

0.018

0.078

0.079

0.2

0.24

HistGradientBoostingRegressor

b-reg

default

OK 15/1

0.0049

0.011

0.075

0.58

2.1

0.0041

0.0054

0.01

0.011

0.073

0.076

0.58

0.58

2.1

2.1

HistGradientBoostingRegressor

~b-reg-64

default

OK 15/

0.0049

0.01

0.045

0.32

1.2

0.004

0.0052

0.01

0.011

0.044

0.045

0.32

0.32

1.1

1.2

HistGradientBoostingRegressor

~b-reg-nan

default

OK 15/1

0.0048

0.011

0.074

0.56

2.1

0.004

0.0051

0.0091

0.012

0.072

0.075

0.55

0.57

2

2.1

HistGradientBoostingRegressor

~b-reg-nan-64

default

OK 15/

0.0047

0.011

0.045

0.32

1.1

0.0041

0.0051

0.0081

0.011

0.043

0.046

0.32

0.32

1.1

1.2

IncrementalPCA#

name

problem

scenario

optim

opset15

onx_nnodes

IncrementalPCA

num-tr

default

OK 13/

2

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

IncrementalPCA

num-tr

default

OK 13/

1.0.2

1

3.3e+02

2

2

skl2onnx

1.1

3.3e+02

2

2

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

IncrementalPCA

num-tr

default

OK 13/

0.29

0.3

0.33

0.4

0.49

0.27

0.31

0.28

0.32

0.29

0.36

0.37

0.42

0.49

0.49

IsotonicRegression#

name

problem

scenario

optim

opset15

onx_nnodes

IsotonicRegression

~b-reg-1d

default

IsotonicRegression

~num+y-tr-1d

default

name

problem

scenario

optim

opset15

ERROR-msg

IsotonicRegression

~b-reg-1d

default

NO CONVERTER

IsotonicRegression

~num+y-tr-1d

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

IsotonicRegression

~b-reg-1d

default

1.0.2

1

IsotonicRegression

~num+y-tr-1d

default

1.0.2

1

IterativeImputer#

name

problem

scenario

optim

opset15

onx_nnodes

IterativeImputer

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

IterativeImputer

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

IterativeImputer

num-tr

default

1.0.2

1

KBinsDiscretizer#

name

problem

scenario

optim

opset15

onx_nnodes

KBinsDiscretizer

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

KBinsDiscretizer

num-tr

default

onehot encoding not supported. ONNX does not support sparse tensors. with o…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

KBinsDiscretizer

num-tr

default

1.0.2

1

KMeans#

name

problem

scenario

optim

opset15

onx_nnodes

KMeans

cluster

default

OK 14/

7

KMeans

~b-clu-64

default

OK 14/

7

KMeans

~num-tr-clu

default

OK 14/

7

KMeans

~num-tr-clu-64

default

OK 14/

7

MiniBatchKMeans

cluster

default

OK 14/

7

MiniBatchKMeans

~b-clu-64

default

OK 14/

7

MiniBatchKMeans

~num-tr-clu

default

OK 14/

7

MiniBatchKMeans

~num-tr-clu-64

default

OK 14/

7

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

KMeans

cluster

default

OK 14/

1.0.2

1

7.6e+02

7

3

skl2onnx

1.1

7.6e+02

7

3

KMeans

~b-clu-64

default

OK 14/

1.0.2

1

9.2e+02

7

3

skl2onnx

1.1

9.2e+02

7

3

KMeans

~num-tr-clu

default

OK 14/

1.0.2

1

7.6e+02

7

3

skl2onnx

1.1

7.6e+02

7

3

KMeans

~num-tr-clu-64

default

OK 14/

1.0.2

1

9.2e+02

7

3

skl2onnx

1.1

9.2e+02

7

3

MiniBatchKMeans

cluster

default

OK 14/

1.0.2

1

7.7e+02

7

3

skl2onnx

1.1

7.7e+02

7

3

MiniBatchKMeans

~b-clu-64

default

OK 14/

1.0.2

1

9.3e+02

7

3

skl2onnx

1.1

9.3e+02

7

3

MiniBatchKMeans

~num-tr-clu

default

OK 14/

1.0.2

1

7.7e+02

7

3

skl2onnx

1.1

7.7e+02

7

3

MiniBatchKMeans

~num-tr-clu-64

default

OK 14/

1.0.2

1

9.3e+02

7

3

skl2onnx

1.1

9.3e+02

7

3

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

KMeans

cluster

default

OK 14/

0.19

0.23

0.29

0.1

1.7

0.04

0.25

0.091

0.26

0.28

0.31

0.083

0.14

1.5

2

KMeans

~b-clu-64

default

OK 14/

0.23

0.22

0.31

0.15

4.2

0.22

0.24

0.07

0.26

0.29

0.34

0.13

0.18

4.1

4.3

KMeans

~num-tr-clu

default

OK 14/

0.34

0.36

0.39

0.51

0.62

0.34

0.36

0.34

0.37

0.36

0.43

0.49

0.53

0.62

0.62

KMeans

~num-tr-clu-64

default

OK 14/

0.41

0.42

0.49

0.76

1.7

0.4

0.44

0.41

0.45

0.47

0.52

0.72

0.81

1.7

1.7

MiniBatchKMeans

cluster

default

OK 14/

0.23

0.25

0.29

0.12

2

0.19

0.24

0.24

0.26

0.27

0.3

0.092

0.15

1.9

2.1

MiniBatchKMeans

~b-clu-64

default

OK 14/

0.23

0.24

0.3

0.12

5.9

0.22

0.24

0.22

0.25

0.28

0.31

0.077

0.17

4.5

7.6

MiniBatchKMeans

~num-tr-clu

default

OK 14/

0.34

0.35

0.39

0.52

0.63

0.32

0.36

0.34

0.37

0.37

0.41

0.5

0.55

0.62

0.63

MiniBatchKMeans

~num-tr-clu-64

default

OK 14/

0.41

0.42

0.49

0.77

1.8

0.4

0.43

0.4

0.44

0.46

0.52

0.75

0.79

1.8

1.8

KNNImputer#

name

problem

scenario

optim

opset15

onx_nnodes

KNNImputer

num-tr

default

OK 15/1

37

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

KNNImputer

num-tr

default

OK 15/1

1.0.2

1

1.2e+04

37

10

skl2onnx

1.1

1

1.2e+04

35

10

1

6

2

1

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

KNNImputer

num-tr

default

OK 15/1

58

59

64

1.7e+02

3.6e+02

56

59

58

60

59

69

1.4e+02

1.9e+02

3.4e+02

3.8e+02

KernelCenterer#

name

problem

scenario

optim

opset15

onx_nnodes

KernelCenterer

num-tr

default

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

KernelCenterer

num-tr

default

ERR: 1training_time

Kernel matrix must be a square matrix. Input is a 112x4 matrix.

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

KernelCenterer

num-tr

default

ERR: 1training_time

1.0.2

KernelPCA#

name

problem

scenario

optim

opset15

onx_nnodes

KernelPCA

num-tr

default

e<0.1 14/

8

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

KernelPCA

num-tr

default

e<0.1 14/

1.0.2

1

5.6e+03

8

6

skl2onnx

1.1

5.6e+03

8

6

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

KernelPCA

num-tr

default

e<0.1 14/

0.018

0.02

0.03

0.096

0.63

0.017

0.019

0.02

0.022

0.028

0.033

0.065

0.12

0.62

0.63

Label…#

name

problem

scenario

optim

opset15

onx_nnodes

LabelBinarizer

int-col

default

OK 13/

4

LabelEncoder

int-col

default

OK 15/2

1

LabelPropagation

b-cl

default

LabelPropagation

m-cl

default

LabelSpreading

b-cl

default

LabelSpreading

m-cl

default

name

problem

scenario

optim

opset15

ERROR-msg

LabelPropagation

b-cl

default

NO CONVERTER

LabelPropagation

m-cl

default

NO CONVERTER

LabelSpreading

b-cl

default

NO CONVERTER

LabelSpreading

m-cl

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

LabelBinarizer

int-col

default

OK 13/

1.0.2

1

5e+02

4

4

skl2onnx

1.1

5e+02

4

4

1

1

LabelEncoder

int-col

default

OK 15/2

1.0.2

1

2.3e+02

1

0

skl2onnx

1.1

2

2.3e+02

1

0

LabelPropagation

b-cl

default

1.0.2

1

LabelPropagation

m-cl

default

1.0.2

1

LabelSpreading

b-cl

default

1.0.2

1

LabelSpreading

m-cl

default

1.0.2

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

LabelBinarizer

int-col

default

OK 13/

0.11

0.12

0.13

0.18

0.45

0.11

0.12

0.11

0.12

0.12

0.14

0.18

0.2

0.43

0.46

LabelEncoder

int-col

default

OK 15/2

0.088

0.13

0.51

4.1

17

0.085

0.096

0.13

0.15

0.47

0.54

3.9

4.3

16

17

LatentDirichletAllocation#

name

problem

scenario

optim

opset15

onx_nnodes

LatentDirichletAllocation

num-tr-pos

default

name

problem

scenario

optim

opset15

ERROR-msg

LatentDirichletAllocation

num-tr-pos

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

LatentDirichletAllocation

num-tr-pos

default

1.0.2

1

Linear#

name

problem

scenario

optim

opset15

onx_nnodes

ARDRegression

b-reg

default

OK 15/1

1

ARDRegression

~b-reg-64

default

OK 13/

3

BayesianRidge

b-reg

default

OK 15/1

1

BayesianRidge

~b-reg-64

default

OK 13/

3

ElasticNet

b-reg

default

OK 15/1

1

ElasticNet

m-reg

default

OK 15/1

1

ElasticNet

~b-reg-64

default

OK 13/

3

ElasticNet

~m-reg-64

default

OK 13/

3

ElasticNetCV

b-reg

default

OK 15/1

1

ElasticNetCV

~b-reg-64

default

OK 13/

3

HuberRegressor

b-reg

default

OK 15/1

1

HuberRegressor

~b-reg-64

default

OK 13/

3

KernelRidge

b-reg

default

KernelRidge

m-reg

default

KernelRidge

~b-reg-64

default

KernelRidge

~m-reg-64

default

Lars

b-reg

default

OK 15/1

1

Lars

m-reg

default

OK 15/1

1

Lars

~b-reg-64

default

OK 13/

3

Lars

~m-reg-64

default

OK 13/

3

LarsCV

b-reg

default

OK 15/1

1

LarsCV

~b-reg-64

default

OK 13/

3

Lasso

b-reg

default

OK 15/1

1

Lasso

m-reg

default

OK 15/1

1

Lasso

~b-reg-64

default

OK 13/

3

Lasso

~m-reg-64

default

OK 13/

3

LassoCV

b-reg

default

OK 15/1

1

LassoCV

~b-reg-64

default

OK 13/

3

LassoLars

b-reg

default

OK 15/1

1

LassoLars

m-reg

default

OK 15/1

1

LassoLars

~b-reg-64

default

OK 13/

3

LassoLars

~m-reg-64

default

OK 13/

3

LassoLarsCV

b-reg

default

OK 15/1

1

LassoLarsCV

~b-reg-64

default

OK 13/

3

LassoLarsIC

b-reg

default

OK 15/1

1

LassoLarsIC

~b-reg-64

default

OK 13/

3

LinearRegression

b-reg

default

OK 15/1

1

LinearRegression

m-reg

default

OK 15/1

1

LinearRegression

~b-reg-64

default

OK 13/

3

LinearRegression

~m-reg-64

default

OK 13/

3

LogisticRegression

b-cl

liblinear

OK 9/1

4

LogisticRegression

b-cl

liblinear

{‘zipmap’: False}

OK 15/1

2

LogisticRegression

b-cl

liblinear

onnx

OK 9/1

4

LogisticRegression

b-cl

liblinear

onnx/{‘zipmap’: False}

OK 15/1

2

LogisticRegression

m-cl

liblinear

OK 9/1

4

LogisticRegression

m-cl

liblinear

{‘zipmap’: False}

OK 15/1

2

LogisticRegression

m-cl

liblinear

onnx

OK 9/1

4

LogisticRegression

m-cl

liblinear

onnx/{‘zipmap’: False}

OK 15/1

2

LogisticRegression

~b-cl-64

liblinear

OK 13/1

13

LogisticRegression

~b-cl-64

liblinear

{‘zipmap’: False}

OK 13/1

11

LogisticRegression

~b-cl-64

liblinear

onnx

OK 13/1

13

LogisticRegression

~b-cl-64

liblinear

onnx/{‘zipmap’: False}

OK 13/1

11

LogisticRegression

~b-cl-dec

liblinear-dec

{‘raw_scores’: True, ‘zipmap’: False}

OK 15/1

1

LogisticRegression

~m-cl-dec

liblinear-dec

{‘raw_scores’: True, ‘zipmap’: False}

OK 15/1

1

LogisticRegressionCV

b-cl

default

{‘zipmap’: False}

OK 15/1

2

LogisticRegressionCV

m-cl

default

{‘zipmap’: False}

OK 15/1

2

MultiTaskElasticNet

m-reg

default

OK 15/1

1

MultiTaskElasticNetCV

m-reg

default

OK 15/1

1

MultiTaskLasso

m-reg

default

OK 15/1

1

MultiTaskLassoCV

m-reg

default

OK 15/1

1

Ridge

b-reg

default

OK 15/1

1

Ridge

m-reg

default

OK 15/1

1

Ridge

~b-reg-64

default

OK 13/

3

Ridge

~m-reg-64

default

OK 13/

3

RidgeCV

b-reg

default

OK 15/1

1

RidgeCV

m-reg

default

OK 15/1

1

RidgeCV

~b-reg-64

default

OK 13/

3

RidgeCV

~m-reg-64

default

OK 13/

3

RidgeClassifier

~b-cl-nop

default

{‘zipmap’: False}

OK 15/1

2

RidgeClassifier

~m-cl-nop

default

{‘zipmap’: False}

OK 15/1

1

RidgeClassifier

~m-label

default

ERR: 2skl_meth

-1

RidgeClassifierCV

~b-cl-nop

default

{‘zipmap’: False}

OK 15/1

2

RidgeClassifierCV

~m-cl-nop

default

{‘zipmap’: False}

OK 15/1

1

RidgeClassifierCV

~m-label

default

ERR: 2skl_meth

-1

SGDClassifier

b-cl

log

{‘zipmap’: False}

OK 14/1

9

SGDClassifier

m-cl

log

{‘zipmap’: False}

ERR: ERROR->=1.0-13/1

18

SGDClassifier

~b-cl-64

log

{‘zipmap’: False}

OK 14/1

9

SGDClassifier

~b-cl-nan

log

ERR: 1training_time

-1

SGDRegressor

b-reg

default

OK 15/1

1

SGDRegressor

~b-reg-64

default

OK 13/

3

TheilSenRegressor

b-reg

default

OK 15/1

1

TheilSenRegressor

~b-reg-64

default

OK 13/

3

name

problem

scenario

optim

opset15

ERROR-msg

KernelRidge

b-reg

default

NO CONVERTER

KernelRidge

m-reg

default

NO CONVERTER

KernelRidge

~b-reg-64

default

NO CONVERTER

KernelRidge

~m-reg-64

default

NO CONVERTER

RidgeClassifier

~m-label

default

ERR: 2skl_meth

‘RidgeClassifier’ object has no attribute ‘predict_proba’

RidgeClassifierCV

~m-label

default

ERR: 2skl_meth

‘RidgeClassifierCV’ object has no attribute ‘predict_proba’

SGDClassifier

~b-cl-nan

log

ERR: 1training_time

Input contains NaN, infinity or a value too large for dtype(‘float64’).

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

ARDRegression

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

ARDRegression

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

BayesianRidge

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

BayesianRidge

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

ElasticNet

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

ElasticNet

m-reg

default

OK 15/1

1.0.2

1

2

1

2.9e+02

1

0

skl2onnx

1.1

1

2.9e+02

1

0

-1

ElasticNet

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

ElasticNet

~m-reg-64

default

OK 13/

1.0.2

1

2

1

4e+02

3

3

skl2onnx

1.1

-1

4e+02

3

3

1

ElasticNetCV

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

ElasticNetCV

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

HuberRegressor

b-reg

default

OK 15/1

1.0.2

1

4

1

2.6e+02

1

0

skl2onnx

1.1

1

2.6e+02

1

0

-1

HuberRegressor

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

KernelRidge

b-reg

default

1.0.2

1

KernelRidge

m-reg

default

1.0.2

1

KernelRidge

~b-reg-64

default

1.0.2

1

KernelRidge

~m-reg-64

default

1.0.2

1

Lars

b-reg

default

OK 15/1

1.0.2

1

4

1

2.4e+02

1

0

skl2onnx

1.1

1

2.4e+02

1

0

-1

Lars

m-reg

default

OK 15/1

1.0.2

1

2

1

2.9e+02

1

0

skl2onnx

1.1

1

2.9e+02

1

0

-1

Lars

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.5e+02

3

3

skl2onnx

1.1

-1

3.5e+02

3

3

1

Lars

~m-reg-64

default

OK 13/

1.0.2

1

2

1

3.9e+02

3

3

skl2onnx

1.1

-1

3.9e+02

3

3

1

LarsCV

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

LarsCV

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.5e+02

3

3

skl2onnx

1.1

-1

3.5e+02

3

3

1

Lasso

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

Lasso

m-reg

default

OK 15/1

1.0.2

1

2

1

2.9e+02

1

0

skl2onnx

1.1

1

2.9e+02

1

0

-1

Lasso

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.5e+02

3

3

skl2onnx

1.1

-1

3.5e+02

3

3

1

Lasso

~m-reg-64

default

OK 13/

1.0.2

1

2

1

3.9e+02

3

3

skl2onnx

1.1

-1

3.9e+02

3

3

1

LassoCV

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

LassoCV

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.5e+02

3

3

skl2onnx

1.1

-1

3.5e+02

3

3

1

LassoLars

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

LassoLars

m-reg

default

OK 15/1

1.0.2

1

2

1

2.9e+02

1

0

skl2onnx

1.1

1

2.9e+02

1

0

-1

LassoLars

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

LassoLars

~m-reg-64

default

OK 13/

1.0.2

1

2

1

4e+02

3

3

skl2onnx

1.1

-1

4e+02

3

3

1

LassoLarsCV

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

LassoLarsCV

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

LassoLarsIC

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

LassoLarsIC

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

LinearRegression

b-reg

default

OK 15/1

1.0.2

1

4

1

2.6e+02

1

0

skl2onnx

1.1

1

2.6e+02

1

0

-1

LinearRegression

m-reg

default

OK 15/1

1.0.2

1

2

1

3e+02

1

0

skl2onnx

1.1

1

3e+02

1

0

-1

LinearRegression

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

LinearRegression

~m-reg-64

default

OK 13/

1.0.2

1

2

1

4e+02

3

3

skl2onnx

1.1

-1

4e+02

3

3

1

LogisticRegression

b-cl

liblinear

OK 9/1

1.0.2

1

1

1

6.5e+02

4

0

skl2onnx

1.1

1

6.5e+02

4

0

-1

1

1

LogisticRegression

b-cl

liblinear

{‘zipmap’: False}

OK 15/1

1.0.2

1

1

1

4.9e+02

2

0

skl2onnx

1.1

1

4.9e+02

2

0

-1

-1

-1

LogisticRegression

b-cl

liblinear

onnx

OK 9/1

1.0.2

1

1

1

6.5e+02

4

0

skl2onnx

1.1

1

6.5e+02

4

0

-1

1

1

LogisticRegression

b-cl

liblinear

onnx/{‘zipmap’: False}

OK 15/1

1.0.2

1

1

1

4.9e+02

2

0

skl2onnx

1.1

1

4.9e+02

2

0

-1

-1

-1

LogisticRegression

m-cl

liblinear

OK 9/1

1.0.2

1

3

1

6.8e+02

4

0

skl2onnx

1.1

1

6.8e+02

4

0

-1

1

1

LogisticRegression

m-cl

liblinear

{‘zipmap’: False}

OK 15/1

1.0.2

1

3

1

5.2e+02

2

0

skl2onnx

1.1

1

5.2e+02

2

0

-1

-1

-1

LogisticRegression

m-cl

liblinear

onnx

OK 9/1

1.0.2

1

3

1

6.8e+02

4

0

skl2onnx

1.1

1

6.8e+02

4

0

-1

1

1

LogisticRegression

m-cl

liblinear

onnx/{‘zipmap’: False}

OK 15/1

1.0.2

1

3

1

5.2e+02

2

0

skl2onnx

1.1

1

5.2e+02

2

0

-1

-1

-1

LogisticRegression

~b-cl-64

liblinear

OK 13/1

1.0.2

1

1

1

1.2e+03

13

5

skl2onnx

1.1

1

1.2e+03

13

5

1

3

1

LogisticRegression

~b-cl-64

liblinear

{‘zipmap’: False}

OK 13/1

1.0.2

1

1

1

1e+03

11

5

skl2onnx

1.1

1

1e+03

11

5

1

2

-1

LogisticRegression

~b-cl-64

liblinear

onnx

OK 13/1

1.0.2

1

1

1

1.2e+03

13

5

skl2onnx

1.1

1

1.2e+03

13

5

1

3

1

LogisticRegression

~b-cl-64

liblinear

onnx/{‘zipmap’: False}

OK 13/1

1.0.2

1

1

1

1e+03

11

5

skl2onnx

1.1

1

1e+03

11

5

1

2

-1

LogisticRegression

~b-cl-dec

liblinear-dec

{‘raw_scores’: True, ‘zipmap’: False}

OK 15/1

1.0.2

1

1

1

4e+02

1

0

skl2onnx

1.1

1

4e+02

1

0

-1

-1

-1

LogisticRegression

~m-cl-dec

liblinear-dec

{‘raw_scores’: True, ‘zipmap’: False}

OK 15/1

1.0.2

1

3

1

4.2e+02

1

0

skl2onnx

1.1

1

4.2e+02

1

0

-1

-1

-1

LogisticRegressionCV

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1

1

5e+02

2

0

skl2onnx

1.1

1

5e+02

2

0

LogisticRegressionCV

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

3

1

5.2e+02

2

0

skl2onnx

1.1

1

5.2e+02

2

0

MultiTaskElasticNet

m-reg

default

OK 15/1

1.0.2

1

2

1

3e+02

1

0

skl2onnx

1.1

1

3e+02

1

0

MultiTaskElasticNetCV

m-reg

default

OK 15/1

1.0.2

1

2

1

3e+02

1

0

skl2onnx

1.1

1

3e+02

1

0

MultiTaskLasso

m-reg

default

OK 15/1

1.0.2

1

2

1

3e+02

1

0

skl2onnx

1.1

1

3e+02

1

0

MultiTaskLassoCV

m-reg

default

OK 15/1

1.0.2

1

2

1

3e+02

1

0

skl2onnx

1.1

1

3e+02

1

0

Ridge

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

Ridge

m-reg

default

OK 15/1

1.0.2

1

2

1

2.9e+02

1

0

skl2onnx

1.1

1

2.9e+02

1

0

-1

Ridge

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.5e+02

3

3

skl2onnx

1.1

-1

3.5e+02

3

3

1

Ridge

~m-reg-64

default

OK 13/

1.0.2

1

2

1

3.9e+02

3

3

skl2onnx

1.1

-1

3.9e+02

3

3

1

RidgeCV

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

RidgeCV

m-reg

default

OK 15/1

1.0.2

1

2

1

2.9e+02

1

0

skl2onnx

1.1

1

2.9e+02

1

0

-1

RidgeCV

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.5e+02

3

3

skl2onnx

1.1

-1

3.5e+02

3

3

1

RidgeCV

~m-reg-64

default

OK 13/

1.0.2

1

2

1

3.9e+02

3

3

skl2onnx

1.1

-1

3.9e+02

3

3

1

RidgeClassifier

~b-cl-nop

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1

1

5.4e+02

2

1

skl2onnx

1.1

1

5.4e+02

2

1

RidgeClassifier

~m-cl-nop

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

3

1

4.2e+02

1

0

skl2onnx

1.1

1

4.2e+02

1

0

RidgeClassifier

~m-label

default

ERR: 2skl_meth

1.0.2

1

3

1

-1

-1

-1

-1

-1

-1

-1

RidgeClassifierCV

~b-cl-nop

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1

1

5.4e+02

2

1

skl2onnx

1.1

1

5.4e+02

2

1

RidgeClassifierCV

~m-cl-nop

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

3

1

4.2e+02

1

0

skl2onnx

1.1

1

4.2e+02

1

0

RidgeClassifierCV

~m-label

default

ERR: 2skl_meth

1.0.2

1

3

1

-1

-1

-1

-1

-1

-1

-1

SGDClassifier

b-cl

log

{‘zipmap’: False}

OK 14/1

1.0.2

1

1

1

8.1e+02

9

5

skl2onnx

1.1

1

8.1e+02

9

5

1

1

SGDClassifier

m-cl

log

{‘zipmap’: False}

ERR: ERROR->=1.0-13/1

1.0.2

1

3

1

1.4e+03

18

8

skl2onnx

1.1

1

1.4e+03

18

8

1

3

SGDClassifier

~b-cl-64

log

{‘zipmap’: False}

OK 14/1

1.0.2

1

1

1

8.3e+02

9

5

skl2onnx

1.1

1

8.3e+02

9

5

1

1

SGDClassifier

~b-cl-nan

log

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

SGDRegressor

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

SGDRegressor

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

TheilSenRegressor

b-reg

default

OK 15/1

1.0.2

1

4

1

2.6e+02

1

0

skl2onnx

1.1

1

2.6e+02

1

0

-1

TheilSenRegressor

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

ARDRegression

b-reg

default

OK 15/1

0.25

0.25

0.25

0.29

0.21

0.24

0.25

0.24

0.25

0.24

0.25

0.28

0.29

0.2

0.22

ARDRegression

~b-reg-64

default

OK 13/

0.7

0.69

0.69

0.71

0.73

0.69

0.71

0.69

0.7

0.68

0.71

0.68

0.75

0.69

0.77

BayesianRidge

b-reg

default

OK 15/1

0.24

0.24

0.25

0.28

0.21

0.24

0.25

0.24

0.25

0.24

0.26

0.27

0.29

0.2

0.22

BayesianRidge

~b-reg-64

default

OK 13/

0.69

0.68

0.68

0.68

0.73

0.68

0.7

0.67

0.68

0.66

0.69

0.66

0.71

0.69

0.77

ElasticNet

b-reg

default

OK 15/1

0.23

0.23

0.24

0.28

0.37

0.22

0.24

0.23

0.23

0.23

0.24

0.27

0.29

0.35

0.4

ElasticNet

m-reg

default

OK 15/1

0.23

0.24

0.26

0.38

0.72

0.23

0.23

0.24

0.25

0.25

0.27

0.37

0.39

0.7

0.74

ElasticNet

~b-reg-64

default

OK 13/

0.63

0.63

0.63

0.64

0.68

0.63

0.64

0.62

0.63

0.61

0.63

0.62

0.66

0.64

0.71

ElasticNet

~m-reg-64

default

OK 13/

0.63

0.62

0.64

0.7

0.87

0.62

0.63

0.6

0.64

0.63

0.66

0.68

0.71

0.86

0.89

ElasticNetCV

b-reg

default

OK 15/1

0.25

0.25

0.26

0.3

0.35

0.24

0.25

0.25

0.25

0.25

0.26

0.29

0.31

0.31

0.4

ElasticNetCV

~b-reg-64

default

OK 13/

0.7

0.69

0.69

0.71

0.69

0.68

0.71

0.68

0.7

0.67

0.71

0.67

0.73

0.64

0.75

HuberRegressor

b-reg

default

OK 15/1

0.26

0.26

0.25

0.29

0.22

0.25

0.26

0.25

0.26

0.21

0.27

0.28

0.31

0.21

0.23

HuberRegressor

~b-reg-64

default

OK 13/

0.73

0.72

0.72

0.73

0.78

0.72

0.74

0.71

0.73

0.71

0.74

0.7

0.76

0.71

0.85

Lars

b-reg

default

OK 15/1

0.26

0.26

0.27

0.31

0.4

0.25

0.27

0.26

0.26

0.26

0.28

0.3

0.32

0.37

0.43

Lars

m-reg

default

OK 15/1

0.26

0.27

0.29

0.43

0.75

0.25

0.26

0.27

0.27

0.28

0.3

0.42

0.45

0.73

0.77

Lars

~b-reg-64

default

OK 13/

0.71

0.7

0.7

0.72

0.76

0.7

0.72

0.7

0.71

0.68

0.73

0.7

0.74

0.72

0.81

Lars

~m-reg-64

default

OK 13/

0.7

0.71

0.72

0.78

0.91

0.7

0.71

0.7

0.71

0.7

0.73

0.74

0.8

0.89

0.92

LarsCV

b-reg

default

OK 15/1

0.25

0.25

0.25

0.3

0.38

0.24

0.26

0.25

0.25

0.25

0.27

0.28

0.32

0.36

0.4

LarsCV

~b-reg-64

default

OK 13/

0.68

0.67

0.67

0.69

0.73

0.67

0.69

0.66

0.68

0.66

0.7

0.65

0.72

0.65

0.82

Lasso

b-reg

default

OK 15/1

0.23

0.23

0.24

0.28

0.35

0.22

0.24

0.23

0.23

0.23

0.25

0.27

0.29

0.32

0.39

Lasso

m-reg

default

OK 15/1

0.23

0.24

0.26

0.38

0.73

0.23

0.23

0.24

0.24

0.25

0.27

0.38

0.4

0.72

0.74

Lasso

~b-reg-64

default

OK 13/

0.63

0.62

0.63

0.63

0.68

0.62

0.64

0.62

0.63

0.61

0.65

0.62

0.66

0.64

0.73

Lasso

~m-reg-64

default

OK 13/

0.62

0.63

0.64

0.71

0.88

0.62

0.62

0.63

0.63

0.63

0.66

0.68

0.73

0.88

0.89

LassoCV

b-reg

default

OK 15/1

0.26

0.26

0.26

0.31

0.45

0.25

0.26

0.25

0.26

0.25

0.27

0.3

0.32

0.42

0.48

LassoCV

~b-reg-64

default

OK 13/

0.7

0.7

0.7

0.72

0.73

0.69

0.71

0.69

0.7

0.68

0.72

0.7

0.75

0.67

0.8

LassoLars

b-reg

default

OK 15/1

0.26

0.26

0.26

0.31

0.4

0.25

0.26

0.26

0.26

0.25

0.27

0.3

0.32

0.38

0.43

LassoLars

m-reg

default

OK 15/1

0.26

0.27

0.29

0.42

0.76

0.26

0.26

0.27

0.27

0.28

0.3

0.41

0.44

0.74

0.77

LassoLars

~b-reg-64

default

OK 13/

0.71

0.7

0.7

0.71

0.78

0.7

0.72

0.7

0.7

0.69

0.72

0.68

0.74

0.74

0.82

LassoLars

~m-reg-64

default

OK 13/

0.7

0.71

0.72

0.78

0.9

0.7

0.71

0.71

0.72

0.71

0.74

0.74

0.8

0.89

0.92

LassoLarsCV

b-reg

default

OK 15/1

0.25

0.25

0.26

0.31

0.39

0.17

0.26

0.25

0.26

0.25

0.27

0.29

0.32

0.37

0.42

LassoLarsCV

~b-reg-64

default

OK 13/

0.69

0.68

0.68

0.7

0.7

0.68

0.7

0.68

0.69

0.67

0.7

0.67

0.72

0.63

0.78

LassoLarsIC

b-reg

default

OK 15/1

0.26

0.26

0.26

0.31

0.39

0.25

0.27

0.26

0.26

0.26

0.28

0.3

0.32

0.35

0.44

LassoLarsIC

~b-reg-64

default

OK 13/

0.71

0.7

0.7

0.72

0.73

0.7

0.72

0.69

0.7

0.68

0.71

0.68

0.74

0.69

0.77

LinearRegression

b-reg

default

OK 15/1

0.27

0.27

0.27

0.32

0.41

0.25

0.27

0.26

0.27

0.26

0.28

0.31

0.33

0.38

0.44

LinearRegression

m-reg

default

OK 15/1

0.26

0.28

0.3

0.43

0.76

0.26

0.27

0.28

0.28

0.29

0.3

0.42

0.44

0.74

0.78

LinearRegression

~b-reg-64

default

OK 13/

0.73

0.72

0.73

0.74

0.77

0.71

0.74

0.72

0.73

0.71

0.75

0.71

0.76

0.73

0.81

LinearRegression

~m-reg-64

default

OK 13/

0.73

0.73

0.75

0.8

0.92

0.73

0.73

0.73

0.74

0.73

0.76

0.77

0.83

0.9

0.95

LogisticRegression

b-cl

liblinear

OK 9/1

0.52

0.56

0.58

0.91

1.6

0.49

0.54

0.51

0.59

0.49

0.68

0.82

0.96

1.6

1.6

LogisticRegression

b-cl

liblinear

{‘zipmap’: False}

OK 15/1

0.44

0.48

0.51

0.85

1.5

0.42

0.46

0.44

0.53

0.43

0.57

0.76

0.91

1.5

1.5

LogisticRegression

m-cl

liblinear

OK 9/1

0.57

0.57

0.58

0.6

0.63

0.55

0.58

0.55

0.59

0.53

0.62

0.56

0.64

0.63

0.63

LogisticRegression

m-cl

liblinear

{‘zipmap’: False}

OK 15/1

0.49

0.5

0.52

0.57

0.61

0.47

0.5

0.48

0.53

0.47

0.55

0.53

0.61

0.61

0.62

LogisticRegression

~b-cl-64

liblinear

OK 13/1

1.4

1.5

1.7

2.7

5.2

1.3

1.4

1.4

1.6

1.5

1.9

2.6

2.9

5

5.3

LogisticRegression

~b-cl-64

liblinear

{‘zipmap’: False}

OK 13/1

1.3

1.4

1.6

2.5

5.1

1.2

1.3

1.3

1.5

1.4

1.7

2.4

2.7

5

5.2

LogisticRegression

~b-cl-dec

liblinear-dec

{‘raw_scores’: True, ‘zipmap’: False}

OK 15/1

0.36

0.38

0.41

0.62

1.4

0.35

0.38

0.37

0.4

0.38

0.47

0.58

0.66

1.3

1.5

LogisticRegression

~m-cl-dec

liblinear-dec

{‘raw_scores’: True, ‘zipmap’: False}

OK 15/1

0.37

0.39

0.41

0.54

0.8

0.36

0.4

0.37

0.42

0.38

0.44

0.51

0.58

0.77

0.83

LogisticRegressionCV

b-cl

default

{‘zipmap’: False}

OK 15/1

0.43

0.47

0.51

0.86

1.6

0.4

0.44

0.44

0.49

0.47

0.56

0.79

0.94

1.5

1.6

LogisticRegressionCV

m-cl

default

{‘zipmap’: False}

OK 15/1

0.6

0.62

0.65

0.77

0.86

0.59

0.61

0.59

0.64

0.61

0.69

0.74

0.8

0.86

0.87

MultiTaskElasticNet

m-reg

default

OK 15/1

0.23

0.24

0.26

0.39

0.72

0.22

0.24

0.23

0.25

0.26

0.27

0.38

0.4

0.71

0.73

MultiTaskElasticNetCV

m-reg

default

OK 15/1

0.25

0.27

0.29

0.42

0.76

0.24

0.26

0.27

0.27

0.28

0.3

0.4

0.43

0.75

0.77

MultiTaskLasso

m-reg

default

OK 15/1

0.23

0.24

0.26

0.38

0.72

0.22

0.23

0.24

0.24

0.25

0.26

0.37

0.39

0.7

0.73

MultiTaskLassoCV

m-reg

default

OK 15/1

0.25

0.27

0.29

0.42

0.73

0.24

0.26

0.27

0.27

0.28

0.3

0.4

0.43

0.72

0.74

Ridge

b-reg

default

OK 15/1

0.26

0.26

0.27

0.32

0.42

0.25

0.27

0.26

0.26

0.26

0.27

0.31

0.34

0.37

0.47

Ridge

m-reg

default

OK 15/1

0.26

0.27

0.29

0.42

0.76

0.26

0.26

0.27

0.28

0.28

0.3

0.41

0.42

0.74

0.78

Ridge

~b-reg-64

default

OK 13/

0.72

0.71

0.72

0.72

0.77

0.7

0.79

0.7

0.72

0.7

0.73

0.7

0.75

0.71

0.84

Ridge

~m-reg-64

default

OK 13/

0.71

0.72

0.74

0.78

0.92

0.7

0.74

0.71

0.73

0.71

0.78

0.76

0.8

0.9

0.95

RidgeCV

b-reg

default

OK 15/1

0.25

0.25

0.26

0.29

0.22

0.25

0.26

0.25

0.26

0.25

0.27

0.28

0.31

0.2

0.24

RidgeCV

m-reg

default

OK 15/1

0.25

0.27

0.27

0.38

0.54

0.25

0.25

0.26

0.27

0.27

0.29

0.37

0.4

0.54

0.55

RidgeCV

~b-reg-64

default

OK 13/

0.72

0.72

0.72

0.73

0.76

0.71

0.74

0.7

0.72

0.7

0.73

0.7

0.75

0.71

0.81

RidgeCV

~m-reg-64

default

OK 13/

0.72

0.72

0.73

0.76

0.91

0.71

0.72

0.71

0.73

0.71

0.76

0.71

0.81

0.9

0.92

RidgeClassifier

~b-cl-nop

default

{‘zipmap’: False}

OK 15/1

0.68

0.7

0.73

0.91

2

0.66

0.7

0.69

0.72

0.66

0.85

0.85

0.98

1.9

2

RidgeClassifier

~m-cl-nop

default

{‘zipmap’: False}

OK 15/1

0.34

0.35

0.38

0.49

0.73

0.33

0.34

0.34

0.36

0.36

0.43

0.47

0.5

0.71

0.75

RidgeClassifierCV

~b-cl-nop

default

{‘zipmap’: False}

OK 15/1

0.66

0.68

0.7

0.84

1.3

0.64

0.68

0.68

0.69

0.68

0.72

0.8

0.86

1.3

1.4

RidgeClassifierCV

~m-cl-nop

default

{‘zipmap’: False}

OK 15/1

0.33

0.34

0.36

0.45

0.58

0.33

0.33

0.34

0.34

0.35

0.37

0.43

0.46

0.58

0.59

SGDClassifier

b-cl

log

{‘zipmap’: False}

OK 14/1

1

1.1

1.1

1.7

2.9

0.96

1.1

1

1.1

1

1.2

1.6

1.9

2.8

2.9

SGDClassifier

m-cl

log

{‘zipmap’: False}

ERR: ERROR->=1.0-13/1

1.9

1.9

1.9

1.8

1.5

1.8

2

1.8

2.1

1.7

2

1.7

1.8

1.5

1.6

SGDClassifier

~b-cl-64

log

{‘zipmap’: False}

OK 14/1

1

1.1

1.2

1.8

3.2

1

1.1

1

1.1

1.1

1.3

1.7

1.9

3.1

3.2

SGDRegressor

b-reg

default

OK 15/1

0.26

0.25

0.25

0.28

0.2

0.25

0.28

0.24

0.27

0.23

0.26

0.26

0.3

0.18

0.22

SGDRegressor

~b-reg-64

default

OK 13/

0.72

0.7

0.71

0.71

0.76

0.7

0.74

0.65

0.73

0.67

0.76

0.67

0.78

0.6

0.96

TheilSenRegressor

b-reg

default

OK 15/1

0.25

0.25

0.25

0.28

0.2

0.24

0.26

0.24

0.26

0.24

0.27

0.26

0.31

0.19

0.21

TheilSenRegressor

~b-reg-64

default

OK 13/

0.72

0.73

0.72

0.75

0.34

0.71

0.73

0.71

1.1

0.7

0.76

0.71

0.81

0.3

0.39

LinearDiscriminantAnalysis#

name

problem

scenario

optim

opset15

onx_nnodes

LinearDiscriminantAnalysis

b-cl

default

e<0.001 9/1

3

LinearDiscriminantAnalysis

m-cl

default

OK 9/1

3

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

LinearDiscriminantAnalysis

b-cl

default

e<0.001 9/1

1.0.2

1

1

1

5.6e+02

3

0

skl2onnx

1.1

1

5.6e+02

3

0

1

1

LinearDiscriminantAnalysis

m-cl

default

OK 9/1

1.0.2

1

3

1

5.9e+02

3

0

skl2onnx

1.1

1

5.9e+02

3

0

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

LinearDiscriminantAnalysis

b-cl

default

e<0.001 9/1

0.65

0.7

0.79

1.5

4.3

0.59

0.67

0.66

0.73

0.68

0.85

1.4

1.6

4.2

4.5

LinearDiscriminantAnalysis

m-cl

default

OK 9/1

0.5

0.51

0.53

0.63

0.73

0.48

0.51

0.48

0.54

0.51

0.57

0.6

0.65

0.72

0.73

LocalOutlierFactor#

name

problem

scenario

optim

opset15

onx_nnodes

LocalOutlierFactor

outlier

novelty

OK 15/

26

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

LocalOutlierFactor

outlier

novelty

OK 15/

1.0.2

1

1.4e+04

26

13

skl2onnx

1.1

1.4e+04

25

13

1

2

1

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

LocalOutlierFactor

outlier

novelty

OK 15/

1.9

1.4

1.4

2.1

2.3

1.8

1.9

1.3

1.4

1.3

1.4

2

2.2

2.2

2.4

MLP#

name

problem

scenario

optim

opset15

onx_nnodes

MLPClassifier

b-cl

default

{‘zipmap’: False}

OK 14/1

13

MLPClassifier

m-cl

default

{‘zipmap’: False}

OK 14/1

12

MLPClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 14/1

13

MLPClassifier

~m-label

default

{‘zipmap’: False}

OK 14/1

10

MLPRegressor

b-reg

default

OK 14/

7

MLPRegressor

m-reg

default

OK 14/

7

MLPRegressor

~b-reg-64

default

OK 14/

7

MLPRegressor

~m-reg-64

default

OK 14/

7

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

MLPClassifier

b-cl

default

{‘zipmap’: False}

OK 14/1

1.0.2

1

3.6e+03

13

7

skl2onnx

1.1

1

3.6e+03

13

7

1

2

-1

MLPClassifier

m-cl

default

{‘zipmap’: False}

OK 14/1

1.0.2

1

4.3e+03

12

6

skl2onnx

1.1

1

4.2e+03

11

6

1

2

1

MLPClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 14/1

1.0.2

1

6e+03

13

7

skl2onnx

1.1

1

6e+03

13

7

1

2

-1

MLPClassifier

~m-label

default

{‘zipmap’: False}

OK 14/1

1.0.2

1

4e+03

10

4

skl2onnx

1.1

1

4e+03

9

4

-1

2

1

MLPRegressor

b-reg

default

OK 14/

1.0.2

1

3e+03

7

5

skl2onnx

1.1

3e+03

7

5

1

1

MLPRegressor

m-reg

default

OK 14/

1.0.2

1

3.4e+03

7

5

skl2onnx

1.1

3.4e+03

7

5

1

1

MLPRegressor

~b-reg-64

default

OK 14/

1.0.2

1

5.4e+03

7

5

skl2onnx

1.1

5.4e+03

7

5

1

1

MLPRegressor

~m-reg-64

default

OK 14/

1.0.2

1

6.2e+03

7

5

skl2onnx

1.1

6.2e+03

7

5

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

MLPClassifier

b-cl

default

{‘zipmap’: False}

OK 14/1

1

1.1

1.2

2

1.7

1

1.1

1.1

1.2

1.1

1.3

1.2

4.5

1.7

1.8

MLPClassifier

m-cl

default

{‘zipmap’: False}

OK 14/1

1.2

1.2

1.2

1.2

1.2

1.1

1.2

1.2

1.3

1.2

1.3

1.1

1.2

1.2

1.2

MLPClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 14/1

1.1

1.1

1.2

1.1

1.6

1

1.1

1.1

1.2

1.1

1.3

1.1

1.1

1.4

1.8

MLPClassifier

~m-label

default

{‘zipmap’: False}

OK 14/1

0.67

0.76

0.88

1

1

0.65

0.69

0.74

0.79

0.82

0.93

1

1

1

1.1

MLPRegressor

b-reg

default

OK 14/

0.69

0.78

0.85

0.92

1.5

0.66

0.7

0.73

0.81

0.79

0.92

0.73

1

1.4

1.5

MLPRegressor

m-reg

default

OK 14/

0.69

0.78

0.86

1.2

1.7

0.67

0.71

0.73

0.83

0.77

0.91

0.99

1.4

1.7

1.7

MLPRegressor

~b-reg-64

default

OK 14/

0.7

0.78

0.87

0.97

1.6

0.67

0.71

0.74

0.8

0.79

0.93

0.96

0.98

1.4

1.7

MLPRegressor

~m-reg-64

default

OK 14/

0.71

0.79

0.89

0.88

1.7

0.68

0.72

0.75

0.84

0.74

0.99

0.68

1

1.7

1.7

MeanShift#

name

problem

scenario

optim

opset15

onx_nnodes

MeanShift

cluster

default

MeanShift

~b-clu-64

default

name

problem

scenario

optim

opset15

ERROR-msg

MeanShift

cluster

default

NO CONVERTER

MeanShift

~b-clu-64

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

MeanShift

cluster

default

1.0.2

1

MeanShift

~b-clu-64

default

1.0.2

1

MiniBatch…#

name

problem

scenario

optim

opset15

onx_nnodes

MiniBatchDictionaryLearning

num-tr

default

MiniBatchSparsePCA

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

MiniBatchDictionaryLearning

num-tr

default

NO CONVERTER

MiniBatchSparsePCA

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

MiniBatchDictionaryLearning

num-tr

default

1.0.2

1

MiniBatchSparsePCA

num-tr

default

1.0.2

1

MissingIndicator#

name

problem

scenario

optim

opset15

onx_nnodes

MissingIndicator

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

MissingIndicator

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

MissingIndicator

num-tr

default

1.0.2

1

MultiLabelBinarizer#

name

problem

scenario

optim

opset15

onx_nnodes

MultiLabelBinarizer

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

MultiLabelBinarizer

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

MultiLabelBinarizer

num-tr

default

1.0.2

1

MultiOutput#

name

problem

scenario

optim

opset15

onx_nnodes

MultiOutputClassifier

m-cl

logreg

ERR: 1training_time

-1

MultiOutputClassifier

~m-label

logreg

{‘zipmap’: False}

ERR: 8max_rel_diff_batch

11

MultiOutputRegressor

m-reg

linreg

OK 15/1

5

name

problem

scenario

optim

opset15

ERROR-msg

MultiOutputClassifier

m-cl

logreg

ERR: 1training_time

y must have at least two dimensions for multi-output regression but has onl…

MultiOutputClassifier

~m-label

logreg

{‘zipmap’: False}

ERR: 8max_rel_diff_batch

Unable to compute differences between [{3}]-[{3}] [array([[0.96352834, 0.03…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

MultiOutputClassifier

m-cl

logreg

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

MultiOutputClassifier

~m-label

logreg

{‘zipmap’: False}

ERR: 8max_rel_diff_batch

1.0.2

4

3

3

1.6e+03

11

1

skl2onnx

1.1

1

1.6e+03

11

1

3

MultiOutputRegressor

m-reg

linreg

OK 15/1

1.0.2

3

8

2

6.6e+02

5

1

skl2onnx

1.1

1

6.6e+02

5

1

2

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

MultiOutputClassifier

~m-label

logreg

{‘zipmap’: False}

ERR: 8max_rel_diff_batch

0.66

0.74

0.77

1

1.6

0.39

0.7

0.71

0.76

0.74

0.81

1

1.1

1.6

1.6

MultiOutputRegressor

m-reg

linreg

OK 15/1

0.02

0.02

0.021

0.022

0.031

0.019

0.022

0.02

0.023

0.02

0.023

0.022

0.023

0.026

0.036

NMF#

name

problem

scenario

optim

opset15

onx_nnodes

NMF

num-tr-pos

default

name

problem

scenario

optim

opset15

ERROR-msg

NMF

num-tr-pos

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

NMF

num-tr-pos

default

1.0.2

1

NearestCentroid#

name

problem

scenario

optim

opset15

onx_nnodes

NearestCentroid

~b-cl-nop

default

NearestCentroid

~b-cl-nop-64

default

name

problem

scenario

optim

opset15

ERROR-msg

NearestCentroid

~b-cl-nop

default

NO CONVERTER

NearestCentroid

~b-cl-nop-64

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

NearestCentroid

~b-cl-nop

default

1.0.2

1

NearestCentroid

~b-cl-nop-64

default

1.0.2

1

NeighborhoodComponentsAnalysis#

name

problem

scenario

optim

opset15

onx_nnodes

NeighborhoodComponentsAnalysis

num+y-tr

default

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

NeighborhoodComponentsAnalysis

num+y-tr

default

ERR: 1training_time

Unknown label type: ‘continuous’

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

NeighborhoodComponentsAnalysis

num+y-tr

default

ERR: 1training_time

1.0.2

Neighbors#

name

problem

scenario

optim

opset15

onx_nnodes

KNeighborsClassifier

b-cl

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

18

KNeighborsClassifier

b-cl

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

23

KNeighborsClassifier

m-cl

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

21

KNeighborsClassifier

m-cl

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

e<0.1 15/1

27

KNeighborsClassifier

~b-cl-64

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

18

KNeighborsClassifier

~b-cl-64

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

23

KNeighborsClassifier

~m-label

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

54

KNeighborsClassifier

~m-label

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

ERR: ERROR->=0.3-15/1

69

KNeighborsRegressor

b-reg

default_k3

cdist

OK 14/1

7

KNeighborsRegressor

b-reg

weights_k3

cdist

e<0.1 15/1

16

KNeighborsRegressor

m-reg

default_k3

cdist

OK 14/1

8

KNeighborsRegressor

m-reg

weights_k3

cdist

e<0.1 15/1

21

KNeighborsRegressor

~b-reg-64

default_k3

cdist

OK 14/1

7

KNeighborsRegressor

~b-reg-64

weights_k3

cdist

e<0.1 15/1

16

KNeighborsRegressor

~m-reg-64

default_k3

cdist

OK 14/1

8

KNeighborsRegressor

~m-reg-64

weights_k3

cdist

ERR: 6ort_run_batch

21

KNeighborsTransformer

num-tr

default

OK 15/

16

RadiusNeighborsClassifier

~b-cl-nop

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

28

RadiusNeighborsClassifier

~b-cl-nop

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

34

RadiusNeighborsClassifier

~m-cl-nop

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

32

RadiusNeighborsClassifier

~m-cl-nop

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

38

RadiusNeighborsRegressor

b-reg

default_k3

OK 15/1

27

RadiusNeighborsRegressor

b-reg

default_k3

cdist

OK 15/1

21

RadiusNeighborsRegressor

b-reg

weights_k3

cdist

OK 15/1

27

RadiusNeighborsRegressor

m-reg

default_k3

OK 15/1

32

RadiusNeighborsRegressor

m-reg

default_k3

cdist

OK 15/1

26

RadiusNeighborsRegressor

m-reg

weights_k3

cdist

OK 15/1

32

RadiusNeighborsRegressor

~b-reg-64

default_k3

OK 15/1

27

RadiusNeighborsRegressor

~b-reg-64

default_k3

cdist

OK 15/1

21

RadiusNeighborsRegressor

~b-reg-64

weights_k3

cdist

OK 15/1

27

RadiusNeighborsRegressor

~m-reg-64

default_k3

ERR: 6ort_run_batch

32

RadiusNeighborsRegressor

~m-reg-64

default_k3

cdist

ERR: 6ort_run_batch

26

RadiusNeighborsRegressor

~m-reg-64

weights_k3

cdist

ERR: 6ort_run_batch

32

RadiusNeighborsTransformer

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

KNeighborsRegressor

~m-reg-64

weights_k3

cdist

ERR: 6ort_run_batch

x and y should share the same dtype float32 != float64

RadiusNeighborsRegressor

~m-reg-64

default_k3

ERR: 6ort_run_batch

x and y should share the same dtype float32 != float64

RadiusNeighborsRegressor

~m-reg-64

default_k3

cdist

ERR: 6ort_run_batch

x and y should share the same dtype float32 != float64

RadiusNeighborsRegressor

~m-reg-64

weights_k3

cdist

ERR: 6ort_run_batch

x and y should share the same dtype float32 != float64

RadiusNeighborsTransformer

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

KNeighborsClassifier

b-cl

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

3.9e+03

18

8

skl2onnx

1.1

1

3.9e+03

18

8

2

3

1

KNeighborsClassifier

b-cl

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

4.2e+03

23

10

skl2onnx

1.1

1

4.2e+03

23

10

2

3

1

KNeighborsClassifier

m-cl

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

4.1e+03

21

9

skl2onnx

1.1

1

4.1e+03

21

9

2

4

1

KNeighborsClassifier

m-cl

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

e<0.1 15/1

1.0.2

1

4.5e+03

27

11

skl2onnx

1.1

1

4.5e+03

27

11

2

4

1

KNeighborsClassifier

~b-cl-64

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

5.7e+03

18

8

skl2onnx

1.1

1

5.7e+03

18

8

2

3

1

KNeighborsClassifier

~b-cl-64

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

6e+03

23

10

skl2onnx

1.1

1

6e+03

23

10

2

3

1

KNeighborsClassifier

~m-label

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

7.2e+03

54

10

skl2onnx

1.1

1

7.1e+03

52

10

7

7

1

KNeighborsClassifier

~m-label

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

ERR: ERROR->=0.3-15/1

1.0.2

1

8.2e+03

69

13

skl2onnx

1.1

1

8e+03

67

13

7

7

1

KNeighborsRegressor

b-reg

default_k3

cdist

OK 14/1

1.0.2

1

3.1e+03

7

4

skl2onnx

1.1

1

3.1e+03

7

4

1

1

1

KNeighborsRegressor

b-reg

weights_k3

cdist

e<0.1 15/1

1.0.2

1

3.8e+03

16

8

skl2onnx

1.1

1

3.8e+03

16

8

3

1

1

KNeighborsRegressor

m-reg

default_k3

cdist

OK 14/1

1.0.2

1

3.6e+03

8

4

skl2onnx

1.1

1

3.6e+03

8

4

1

1

1

KNeighborsRegressor

m-reg

weights_k3

cdist

e<0.1 15/1

1.0.2

1

4.6e+03

21

9

skl2onnx

1.1

1

4.6e+03

21

9

2

1

1

KNeighborsRegressor

~b-reg-64

default_k3

cdist

OK 14/1

1.0.2

1

5.3e+03

7

4

skl2onnx

1.1

1

5.3e+03

7

4

1

1

1

KNeighborsRegressor

~b-reg-64

weights_k3

cdist

e<0.1 15/1

1.0.2

1

6e+03

16

8

skl2onnx

1.1

1

6e+03

16

8

3

1

1

KNeighborsRegressor

~m-reg-64

default_k3

cdist

OK 14/1

1.0.2

1

6.3e+03

8

4

skl2onnx

1.1

1

6.3e+03

8

4

1

1

1

KNeighborsRegressor

~m-reg-64

weights_k3

cdist

ERR: 6ort_run_batch

1.0.2

1

7.3e+03

21

9

skl2onnx

1.1

1

7.3e+03

21

9

2

1

1

KNeighborsTransformer

num-tr

default

OK 15/

1.0.2

1

3.4e+03

16

6

skl2onnx

1.1

3.3e+03

15

6

2

1

2

1

1

1

RadiusNeighborsClassifier

~b-cl-nop

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

4.5e+03

28

8

skl2onnx

1.1

1

4.5e+03

28

8

2

5

1

RadiusNeighborsClassifier

~b-cl-nop

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

4.9e+03

34

9

skl2onnx

1.1

1

4.9e+03

34

9

2

6

1

RadiusNeighborsClassifier

~m-cl-nop

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

4.8e+03

32

9

skl2onnx

1.1

1

4.8e+03

32

9

2

6

1

RadiusNeighborsClassifier

~m-cl-nop

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

1.0.2

1

5.2e+03

38

10

skl2onnx

1.1

1

5.2e+03

38

10

2

7

1

RadiusNeighborsRegressor

b-reg

default_k3

OK 15/1

1.0.2

1

4.6e+03

27

6

skl2onnx

1.1

1

4.5e+03

26

6

3

3

-1

2

1

1

1

RadiusNeighborsRegressor

b-reg

default_k3

cdist

OK 15/1

1.0.2

1

4.1e+03

21

6

skl2onnx

1.1

1

4.1e+03

21

6

3

3

1

-1

-1

-1

-1

RadiusNeighborsRegressor

b-reg

weights_k3

cdist

OK 15/1

1.0.2

1

4.5e+03

27

7

skl2onnx

1.1

1

4.5e+03

27

7

3

4

1

-1

-1

-1

-1

RadiusNeighborsRegressor

m-reg

default_k3

OK 15/1

1.0.2

1

5.4e+03

32

7

skl2onnx

1.1

1

5.3e+03

31

7

2

3

-1

2

1

1

1

RadiusNeighborsRegressor

m-reg

default_k3

cdist

OK 15/1

1.0.2

1

4.9e+03

26

7

skl2onnx

1.1

1

4.9e+03

26

7

2

3

1

-1

-1

-1

-1

RadiusNeighborsRegressor

m-reg

weights_k3

cdist

OK 15/1

1.0.2

1

5.3e+03

32

8

skl2onnx

1.1

1

5.3e+03

32

8

2

4

1

-1

-1

-1

-1

RadiusNeighborsRegressor

~b-reg-64

default_k3

OK 15/1

1.0.2

1

6.8e+03

27

6

skl2onnx

1.1

1

6.8e+03

26

6

3

3

-1

2

1

1

1

RadiusNeighborsRegressor

~b-reg-64

default_k3

cdist

OK 15/1

1.0.2

1

6.4e+03

21

6

skl2onnx

1.1

1

6.4e+03

21

6

3

3

1

-1

-1

-1

-1

RadiusNeighborsRegressor

~b-reg-64

weights_k3

cdist

OK 15/1

1.0.2

1

6.8e+03

27

7

skl2onnx

1.1

1

6.8e+03

27

7

3

4

1

-1

-1

-1

-1

RadiusNeighborsRegressor

~m-reg-64

default_k3

ERR: 6ort_run_batch

1.0.2

1

8.1e+03

32

7

skl2onnx

1.1

1

8e+03

31

7

2

3

-1

2

1

1

1

RadiusNeighborsRegressor

~m-reg-64

default_k3

cdist

ERR: 6ort_run_batch

1.0.2

1

7.6e+03

26

7

skl2onnx

1.1

1

7.6e+03

26

7

2

3

1

-1

-1

-1

-1

RadiusNeighborsRegressor

~m-reg-64

weights_k3

cdist

ERR: 6ort_run_batch

1.0.2

1

8e+03

32

8

skl2onnx

1.1

1

8e+03

32

8

2

4

1

-1

-1

-1

-1

RadiusNeighborsTransformer

num-tr

default

1.0.2

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

KNeighborsClassifier

b-cl

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.057

0.06

0.078

0.25

0.42

0.055

0.06

0.058

0.063

0.074

0.082

0.22

0.3

0.41

0.43

KNeighborsClassifier

b-cl

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.065

0.068

0.09

0.27

0.44

0.064

0.068

0.067

0.072

0.085

0.12

0.24

0.35

0.43

0.44

KNeighborsClassifier

m-cl

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.062

0.066

0.084

0.24

0.43

0.061

0.065

0.065

0.069

0.082

0.088

0.23

0.24

0.42

0.43

KNeighborsClassifier

m-cl

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

e<0.1 15/1

0.072

0.075

0.096

0.24

0.44

0.07

0.074

0.074

0.079

0.09

0.12

0.24

0.25

0.44

0.44

KNeighborsClassifier

~b-cl-64

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.061

0.065

0.087

0.25

0.45

0.06

0.063

0.064

0.068

0.082

0.09

0.24

0.25

0.45

0.46

KNeighborsClassifier

~b-cl-64

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.071

0.074

0.096

0.25

0.47

0.069

0.074

0.073

0.077

0.092

0.1

0.25

0.26

0.46

0.48

KNeighborsClassifier

~m-label

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.15

0.16

0.18

0.32

0.49

0.15

0.16

0.15

0.16

0.16

0.33

0.31

0.32

0.49

0.5

KNeighborsClassifier

~m-label

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

ERR: ERROR->=0.3-15/1

0.17

0.18

0.2

0.33

0.51

0.17

0.18

0.17

0.18

0.19

0.25

0.33

0.34

0.5

0.52

KNeighborsRegressor

b-reg

default_k3

cdist

OK 14/1

0.029

0.031

0.051

0.21

0.41

0.028

0.031

0.03

0.033

0.049

0.055

0.2

0.21

0.4

0.41

KNeighborsRegressor

b-reg

weights_k3

cdist

e<0.1 15/1

0.051

0.054

0.073

0.22

0.42

0.049

0.053

0.052

0.056

0.067

0.1

0.22

0.23

0.42

0.43

KNeighborsRegressor

m-reg

default_k3

cdist

OK 14/1

0.03

0.033

0.063

0.2

0.4

0.029

0.031

0.032

0.034

0.051

0.15

0.2

0.21

0.4

0.4

KNeighborsRegressor

m-reg

weights_k3

cdist

e<0.1 15/1

0.058

0.061

0.083

0.24

0.44

0.057

0.06

0.059

0.064

0.076

0.1

0.23

0.24

0.44

0.45

KNeighborsRegressor

~b-reg-64

default_k3

cdist

OK 14/1

0.03

0.033

0.059

0.22

0.43

0.029

0.033

0.032

0.035

0.054

0.097

0.21

0.22

0.42

0.44

KNeighborsRegressor

~b-reg-64

weights_k3

cdist

e<0.1 15/1

0.055

0.058

0.084

0.24

0.44

0.054

0.057

0.056

0.06

0.076

0.13

0.24

0.24

0.42

0.47

KNeighborsRegressor

~m-reg-64

default_k3

cdist

OK 14/1

0.032

0.035

0.058

0.21

0.4

0.031

0.033

0.034

0.038

0.056

0.063

0.21

0.22

0.37

0.43

KNeighborsTransformer

num-tr

default

OK 15/

1.8

1.4

1.5

3.4

5.9

1.8

1.9

1.3

1.4

1.4

1.6

3.3

3.5

5.8

5.9

RadiusNeighborsClassifier

~b-cl-nop

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.069

0.074

0.083

0.11

0.16

0.066

0.072

0.071

0.078

0.081

0.086

0.11

0.11

0.16

0.16

RadiusNeighborsClassifier

~b-cl-nop

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.082

0.086

0.087

0.094

0.13

0.08

0.085

0.083

0.089

0.085

0.089

0.094

0.094

0.13

0.13

RadiusNeighborsClassifier

~m-cl-nop

default_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.076

0.08

0.091

0.12

0.18

0.074

0.079

0.078

0.084

0.087

0.094

0.12

0.12

0.18

0.18

RadiusNeighborsClassifier

~m-cl-nop

weights_k3

{‘optim’: ‘cdist’, ‘zipmap’: False}

OK 15/1

0.088

0.091

0.092

0.1

0.14

0.084

0.09

0.089

0.094

0.089

0.096

0.1

0.1

0.14

0.14

RadiusNeighborsRegressor

b-reg

default_k3

OK 15/1

1.1

1.1

0.65

0.21

0.15

1.1

1.2

1

1.1

0.63

0.66

0.21

0.21

0.15

0.15

RadiusNeighborsRegressor

b-reg

default_k3

cdist

OK 15/1

0.055

0.057

0.058

0.06

0.081

0.053

0.057

0.055

0.06

0.056

0.059

0.059

0.061

0.081

0.081

RadiusNeighborsRegressor

b-reg

weights_k3

cdist

OK 15/1

0.065

0.064

0.048

0.04

0.051

0.063

0.068

0.063

0.068

0.047

0.05

0.04

0.04

0.051

0.051

RadiusNeighborsRegressor

m-reg

default_k3

OK 15/1

1.1

1.1

0.64

0.23

0.18

1.1

1.1

1

1.1

0.63

0.65

0.22

0.23

0.18

0.18

RadiusNeighborsRegressor

m-reg

default_k3

cdist

OK 15/1

0.06

0.066

0.07

0.077

0.11

0.058

0.064

0.064

0.068

0.068

0.073

0.076

0.079

0.11

0.11

RadiusNeighborsRegressor

m-reg

weights_k3

cdist

OK 15/1

0.072

0.072

0.055

0.046

0.061

0.069

0.075

0.069

0.077

0.054

0.056

0.046

0.046

0.06

0.062

RadiusNeighborsRegressor

~b-reg-64

default_k3

OK 15/1

1.2

1.2

0.7

0.27

0.24

1.2

1.3

1.1

1.2

0.65

0.72

0.27

0.28

0.24

0.24

RadiusNeighborsRegressor

~b-reg-64

default_k3

cdist

OK 15/1

0.059

0.065

0.082

0.1

0.13

0.057

0.062

0.063

0.067

0.075

0.084

0.1

0.1

0.13

0.13

RadiusNeighborsRegressor

~b-reg-64

weights_k3

cdist

OK 15/1

0.072

0.074

0.071

0.068

0.087

0.071

0.075

0.071

0.077

0.07

0.073

0.068

0.068

0.086

0.088

Nystroem#

name

problem

scenario

optim

opset15

onx_nnodes

Nystroem

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

Nystroem

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

Nystroem

num-tr

default

1.0.2

1

OneHotEncoder#

name

problem

scenario

optim

opset15

onx_nnodes

OneHotEncoder

one-hot

default

OK 11/1

5

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

OneHotEncoder

one-hot

default

OK 11/1

1.0.2

1

5.1e+02

5

2

skl2onnx

1.1

1

5.1e+02

5

2

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

OneHotEncoder

one-hot

default

OK 11/1

0.24

0.34

1.3

9.6

53

0.23

0.24

0.33

0.35

1.2

1.3

9.5

9.8

52

53

OneVs…#

name

problem

scenario

optim

opset15

onx_nnodes

OneVsOneClassifier

~b-cl-nop

logreg

OneVsOneClassifier

~m-cl-nop

logreg

OneVsRestClassifier

b-cl

logreg

{‘zipmap’: False}

OK 15/1

14

OneVsRestClassifier

m-cl

logreg

{‘zipmap’: False}

OK 15/1

18

OneVsRestClassifier

~b-cl-64

logreg

{‘zipmap’: False}

OK 15/1

23

OneVsRestClassifier

~m-label

logreg

{‘zipmap’: False}

OK 15/1

17

name

problem

scenario

optim

opset15

ERROR-msg

OneVsOneClassifier

~b-cl-nop

logreg

NO CONVERTER

OneVsOneClassifier

~m-cl-nop

logreg

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

OneVsOneClassifier

~b-cl-nop

logreg

1.0.2

2

1

1

OneVsOneClassifier

~m-cl-nop

logreg

1.0.2

4

3

3

OneVsRestClassifier

b-cl

logreg

{‘zipmap’: False}

OK 15/1

1.0.2

2

2

2

1.5e+03

14

5

skl2onnx

1.1

1

1.5e+03

14

5

1

3

1

OneVsRestClassifier

m-cl

logreg

{‘zipmap’: False}

OK 15/1

1.0.2

4

6

4

2.1e+03

18

4

skl2onnx

1.1

1

2.1e+03

18

4

1

3

1

OneVsRestClassifier

~b-cl-64

logreg

{‘zipmap’: False}

OK 15/1

1.0.2

2

2

2

1.9e+03

23

7

skl2onnx

1.1

1

1.6e+03

18

7

2

5

1

OneVsRestClassifier

~m-label

logreg

{‘zipmap’: False}

OK 15/1

1.0.2

4

6

4

1.9e+03

17

5

skl2onnx

1.1

1

1.9e+03

17

5

1

2

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

OneVsRestClassifier

b-cl

logreg

{‘zipmap’: False}

OK 15/1

1.3

1.4

1.4

2

3.1

1.3

1.4

1.2

1.5

1.3

1.5

1.9

2.1

3.1

3.1

OneVsRestClassifier

m-cl

logreg

{‘zipmap’: False}

OK 15/1

0.84

0.88

0.95

1.5

2.5

0.81

0.86

0.86

0.91

0.91

0.98

1.4

1.5

2.5

2.5

OneVsRestClassifier

~b-cl-64

logreg

{‘zipmap’: False}

OK 15/1

1.9

2

2.1

3

4.6

1.8

1.9

1.9

2.1

2

2.3

2.9

3.1

4.6

4.7

OneVsRestClassifier

~m-label

logreg

{‘zipmap’: False}

OK 15/1

0.81

0.87

0.9

1.2

1.7

0.79

0.83

0.84

0.89

0.86

0.96

1.2

1.2

1.7

1.7

OrdinalEncoder#

name

problem

scenario

optim

opset15

onx_nnodes

OrdinalEncoder

num-tr

default

ERR: 3prediction

name

problem

scenario

optim

opset15

ERROR-msg

OrdinalEncoder

num-tr

default

ERR: 3prediction

Found unknown categories [4.03909, 4.312008, 4.366583, 4.3827257, 4.5485244…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

OrdinalEncoder

num-tr

default

ERR: 3prediction

1.0.2

1

OrthogonalMatchingPursuit#

name

problem

scenario

optim

opset15

onx_nnodes

OrthogonalMatchingPursuit

b-reg

default

OK 15/1

1

OrthogonalMatchingPursuit

m-reg

default

OK 15/1

1

OrthogonalMatchingPursuit

~b-reg-64

default

OK 13/

3

OrthogonalMatchingPursuit

~m-reg-64

default

OK 13/

3

OrthogonalMatchingPursuitCV

b-reg

default

OK 15/1

1

OrthogonalMatchingPursuitCV

~b-reg-64

default

OK 13/

3

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

OrthogonalMatchingPursuit

b-reg

default

OK 15/1

1.0.2

1

4

1

2.7e+02

1

0

skl2onnx

1.1

1

2.7e+02

1

0

-1

OrthogonalMatchingPursuit

m-reg

default

OK 15/1

1.0.2

1

2

1

3.1e+02

1

0

skl2onnx

1.1

1

3.1e+02

1

0

-1

OrthogonalMatchingPursuit

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.7e+02

3

3

skl2onnx

1.1

-1

3.7e+02

3

3

1

OrthogonalMatchingPursuit

~m-reg-64

default

OK 13/

1.0.2

1

2

1

4.1e+02

3

3

skl2onnx

1.1

-1

4.1e+02

3

3

1

OrthogonalMatchingPursuitCV

b-reg

default

OK 15/1

1.0.2

1

4

1

2.7e+02

1

0

skl2onnx

1.1

1

2.7e+02

1

0

-1

OrthogonalMatchingPursuitCV

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.7e+02

3

3

skl2onnx

1.1

-1

3.7e+02

3

3

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

OrthogonalMatchingPursuit

b-reg

default

OK 15/1

0.26

0.26

0.26

0.3

0.21

0.25

0.26

0.26

0.26

0.25

0.27

0.29

0.31

0.2

0.21

OrthogonalMatchingPursuit

m-reg

default

OK 15/1

0.26

0.27

0.28

0.39

0.55

0.25

0.26

0.25

0.27

0.27

0.29

0.37

0.4

0.55

0.56

OrthogonalMatchingPursuit

~b-reg-64

default

OK 13/

0.74

0.73

0.73

0.75

0.77

0.73

0.75

0.73

0.74

0.72

0.76

0.72

0.77

0.73

0.82

OrthogonalMatchingPursuit

~m-reg-64

default

OK 13/

0.73

0.74

0.75

0.8

0.98

0.71

0.73

0.73

0.74

0.73

0.78

0.76

0.82

0.97

1

OrthogonalMatchingPursuitCV

b-reg

default

OK 15/1

0.25

0.25

0.25

0.29

0.21

0.24

0.26

0.25

0.26

0.25

0.27

0.28

0.3

0.19

0.22

OrthogonalMatchingPursuitCV

~b-reg-64

default

OK 13/

0.72

0.71

0.71

0.72

0.76

0.71

0.73

0.71

0.72

0.69

0.73

0.7

0.74

0.73

0.8

OutputCode#

name

problem

scenario

optim

opset15

onx_nnodes

OutputCodeClassifier

~b-cl-nop

logreg

OutputCodeClassifier

~m-cl-nop

logreg

name

problem

scenario

optim

opset15

ERROR-msg

OutputCodeClassifier

~b-cl-nop

logreg

NO CONVERTER

OutputCodeClassifier

~m-cl-nop

logreg

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

OutputCodeClassifier

~b-cl-nop

logreg

1.0.2

4

1

1

OutputCodeClassifier

~m-cl-nop

logreg

1.0.2

5

3

3

PCA#

name

problem

scenario

optim

opset15

onx_nnodes

PCA

num-tr

default

OK 13/

2

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

PCA

num-tr

default

OK 13/

1.0.2

1

3.2e+02

2

2

skl2onnx

1.1

3.2e+02

2

2

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

PCA

num-tr

default

OK 13/

0.31

0.32

0.35

0.48

0.76

0.29

0.32

0.3

0.34

0.32

0.38

0.44

0.51

0.73

0.79

PLS…#

name

problem

scenario

optim

opset15

onx_nnodes

PLSCanonical

b-reg

default

PLSCanonical

m-reg

default

PLSCanonical

num+y-tr

default

PLSCanonical

~b-reg-64

default

PLSCanonical

~m-reg-64

default

PLSRegression

b-reg

default

OK 14/

4

PLSRegression

m-reg

default

OK 14/

4

PLSRegression

num+y-tr

default

big-diff

4

PLSRegression

~b-reg-64

default

OK 14/

4

PLSRegression

~m-reg-64

default

OK 14/

4

PLSSVD

num+y-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

PLSCanonical

b-reg

default

NO CONVERTER

PLSCanonical

m-reg

default

NO CONVERTER

PLSCanonical

num+y-tr

default

NO CONVERTER

PLSCanonical

~b-reg-64

default

NO CONVERTER

PLSCanonical

~m-reg-64

default

NO CONVERTER

PLSSVD

num+y-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

PLSCanonical

b-reg

default

1.0.2

1

4

1

PLSCanonical

m-reg

default

1.0.2

1

4

1

PLSCanonical

num+y-tr

default

1.0.2

1

4

1

PLSCanonical

~b-reg-64

default

1.0.2

1

4

1

PLSCanonical

~m-reg-64

default

1.0.2

1

4

1

PLSRegression

b-reg

default

OK 14/

1.0.2

1

4

1

4.2e+02

4

4

skl2onnx

1.1

4.2e+02

4

4

PLSRegression

m-reg

default

OK 14/

1.0.2

1

4

1

4.4e+02

4

4

skl2onnx

1.1

4.4e+02

4

4

PLSRegression

num+y-tr

default

big-diff

1.0.2

1

4

1

4.2e+02

4

4

skl2onnx

1.1

4.2e+02

4

4

PLSRegression

~b-reg-64

default

OK 14/

1.0.2

1

4

1

4.8e+02

4

4

skl2onnx

1.1

4.8e+02

4

4

PLSRegression

~m-reg-64

default

OK 14/

1.0.2

1

4

1

5.2e+02

4

4

skl2onnx

1.1

5.2e+02

4

4

PLSSVD

num+y-tr

default

1.0.2

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

PLSRegression

b-reg

default

OK 14/

0.45

0.45

0.45

0.41

0.31

0.36

0.55

0.39

0.58

0.38

0.59

0.36

0.5

0.29

0.33

PLSRegression

m-reg

default

OK 14/

0.43

0.45

0.45

0.43

0.41

0.38

0.45

0.43

0.49

0.38

0.52

0.41

0.45

0.41

0.42

PLSRegression

num+y-tr

default

big-diff

0.48

0.48

0.48

0.42

0.28

0.46

0.51

0.46

0.52

0.44

0.57

0.38

0.45

0.27

0.28

PLSRegression

~b-reg-64

default

OK 14/

0.47

0.48

0.51

0.66

0.86

0.45

0.49

0.46

0.5

0.48

0.56

0.63

0.71

0.84

0.87

PLSRegression

~m-reg-64

default

OK 14/

0.47

0.48

0.52

0.68

0.9

0.45

0.48

0.46

0.5

0.47

0.55

0.64

0.71

0.89

0.91

PassiveAggressive#

name

problem

scenario

optim

opset15

onx_nnodes

PassiveAggressiveClassifier

~b-cl-nop

logreg

{‘zipmap’: False}

OK 13/1

8

PassiveAggressiveClassifier

~m-cl-nop

logreg

{‘zipmap’: False}

OK 14/1

7

PassiveAggressiveRegressor

b-reg

default

OK 15/1

1

PassiveAggressiveRegressor

~b-reg-64

default

OK 13/

3

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

PassiveAggressiveClassifier

~b-cl-nop

logreg

{‘zipmap’: False}

OK 13/1

1.0.2

1

1

1

7.9e+02

8

5

skl2onnx

1.1

1

7.9e+02

8

5

1

1

-1

PassiveAggressiveClassifier

~m-cl-nop

logreg

{‘zipmap’: False}

OK 14/1

1.0.2

1

3

1

7.4e+02

7

4

skl2onnx

1.1

1

7.1e+02

6

4

1

1

1

PassiveAggressiveRegressor

b-reg

default

OK 15/1

1.0.2

1

4

1

2.7e+02

1

0

skl2onnx

1.1

1

2.7e+02

1

0

-1

PassiveAggressiveRegressor

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.7e+02

3

3

skl2onnx

1.1

-1

3.7e+02

3

3

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

PassiveAggressiveClassifier

~b-cl-nop

logreg

{‘zipmap’: False}

OK 13/1

1.3

1.4

1.5

2.2

4.9

1.3

1.4

1.3

1.5

1.3

1.6

2.1

2.3

4.6

5.1

PassiveAggressiveClassifier

~m-cl-nop

logreg

{‘zipmap’: False}

OK 14/1

1.2

1.2

1.3

1.8

2.6

1.1

1.2

1.1

1.3

1.1

1.3

1.7

1.9

2.6

2.7

PassiveAggressiveRegressor

b-reg

default

OK 15/1

0.26

0.24

0.25

0.28

0.23

0.24

0.27

0.24

0.27

0.23

0.28

0.26

0.3

0.2

0.26

PassiveAggressiveRegressor

~b-reg-64

default

OK 13/

0.72

0.7

0.72

0.71

0.75

0.7

0.75

0.65

0.75

0.66

0.77

0.66

0.77

0.62

0.9

Perceptron#

name

problem

scenario

optim

opset15

onx_nnodes

Perceptron

~b-cl-dec

logreg

{‘zipmap’: False}

OK 13/1

8

Perceptron

~b-cl-nop

logreg

{‘zipmap’: False}

OK 13/1

8

Perceptron

~m-cl-dec

logreg

{‘zipmap’: False}

OK 14/1

7

Perceptron

~m-cl-nop

logreg

{‘zipmap’: False}

OK 14/1

7

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

Perceptron

~b-cl-dec

logreg

{‘zipmap’: False}

OK 13/1

1.0.2

1

1

1

7.8e+02

8

5

skl2onnx

1.1

1

7.8e+02

8

5

1

1

-1

Perceptron

~b-cl-nop

logreg

{‘zipmap’: False}

OK 13/1

1.0.2

1

1

1

7.8e+02

8

5

skl2onnx

1.1

1

7.8e+02

8

5

1

1

-1

Perceptron

~m-cl-dec

logreg

{‘zipmap’: False}

OK 14/1

1.0.2

1

3

1

7.3e+02

7

4

skl2onnx

1.1

1

6.9e+02

6

4

1

1

1

Perceptron

~m-cl-nop

logreg

{‘zipmap’: False}

OK 14/1

1.0.2

1

3

1

7.3e+02

7

4

skl2onnx

1.1

1

6.9e+02

6

4

1

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

Perceptron

~b-cl-dec

logreg

{‘zipmap’: False}

OK 13/1

1.5

1.6

1.6

2.7

4.6

1.5

1.6

1.5

1.6

1.3

1.8

2.6

2.9

3.8

5.9

Perceptron

~b-cl-nop

logreg

{‘zipmap’: False}

OK 13/1

1.4

1.4

1.5

2.3

4.9

1.3

1.5

1.3

1.4

1.3

1.6

2.2

2.5

4.8

5

Perceptron

~m-cl-dec

logreg

{‘zipmap’: False}

OK 14/1

1.4

1.4

1.5

2.2

3.5

1.3

1.4

1.3

1.4

1.2

1.6

2.1

2.5

3.3

3.7

Perceptron

~m-cl-nop

logreg

{‘zipmap’: False}

OK 14/1

1.2

1.2

1.3

1.8

2.6

1.1

1.3

1.1

1.4

1.2

1.4

1.7

2

2.5

2.7

Poisson#

name

problem

scenario

optim

opset15

onx_nnodes

PoissonRegressor

b-reg

default

OK 14/

4

PoissonRegressor

m-reg

default

ERR: 1training_time

-1

PoissonRegressor

~b-reg-64

default

OK 14/

4

PoissonRegressor

~m-reg-64

default

ERR: 1training_time

-1

name

problem

scenario

optim

opset15

ERROR-msg

PoissonRegressor

m-reg

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

PoissonRegressor

~m-reg-64

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

PoissonRegressor

b-reg

default

OK 14/

1.0.2

1

4

1

4e+02

4

3

skl2onnx

1.1

4e+02

4

3

1

PoissonRegressor

m-reg

default

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

PoissonRegressor

~b-reg-64

default

OK 14/

1.0.2

1

4

1

4.2e+02

4

3

skl2onnx

1.1

4.2e+02

4

3

1

PoissonRegressor

~m-reg-64

default

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

PoissonRegressor

b-reg

default

OK 14/

0.66

0.7

0.69

0.65

0.45

0.64

0.68

0.67

0.73

0.64

0.77

0.58

0.7

0.42

0.48

PoissonRegressor

~b-reg-64

default

OK 14/

0.69

0.73

0.75

0.8

0.94

0.65

0.71

0.7

0.8

0.69

0.8

0.76

0.87

0.91

0.97

PolynomialCountSketch#

name

problem

scenario

optim

opset15

onx_nnodes

PolynomialCountSketch

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

PolynomialCountSketch

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

PolynomialCountSketch

num-tr

default

1.0.2

1

PolynomialFeatures#

name

problem

scenario

optim

opset15

onx_nnodes

PolynomialFeatures

num-tr

default

OK 15/1

31

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

PolynomialFeatures

num-tr

default

OK 15/1

1.0.2

1

2.5e+03

31

14

skl2onnx

1.1

1

2.5e+03

31

14

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

PolynomialFeatures

num-tr

default

OK 15/1

6.3

5.6

5.4

4.3

2.4

5.9

6.5

5.4

5.7

5

5.5

4.1

4.5

2.4

2.4

PowerTransformer#

name

problem

scenario

optim

opset15

onx_nnodes

PowerTransformer

num-tr-pos

box-cox

OK 15/1

11

PowerTransformer

num-tr-pos

yeo-johnson

OK 15/1

31

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

PowerTransformer

num-tr-pos

box-cox

OK 15/1

1.0.2

1

9.8e+02

11

3

skl2onnx

1.1

1

9.8e+02

11

3

-1

PowerTransformer

num-tr-pos

yeo-johnson

OK 15/1

1.0.2

1

2.2e+03

31

4

skl2onnx

1.1

1

2.2e+03

31

4

2

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

PowerTransformer

num-tr-pos

box-cox

OK 15/1

0.6

0.61

0.63

0.66

0.71

0.58

0.63

0.58

0.62

0.6

0.64

0.64

0.68

0.71

0.71

PowerTransformer

num-tr-pos

yeo-johnson

OK 15/1

0.65

0.66

0.72

1.1

2.5

0.63

0.67

0.65

0.68

0.71

0.74

1

1.1

2.5

2.5

QuadraticDiscriminantAnalysis#

name

problem

scenario

optim

opset15

onx_nnodes

QuadraticDiscriminantAnalysis

b-cl

default

QuadraticDiscriminantAnalysis

m-cl

default

name

problem

scenario

optim

opset15

ERROR-msg

QuadraticDiscriminantAnalysis

b-cl

default

NO CONVERTER

QuadraticDiscriminantAnalysis

m-cl

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

QuadraticDiscriminantAnalysis

b-cl

default

1.0.2

1

QuadraticDiscriminantAnalysis

m-cl

default

1.0.2

1

Quantile#

name

problem

scenario

optim

opset15

onx_nnodes

QuantileRegressor

b-reg

default

OK 15/1

1

QuantileRegressor

m-reg

default

ERR: 1training_time

-1

QuantileRegressor

~b-reg-64

default

OK 13/

3

QuantileRegressor

~m-reg-64

default

ERR: 1training_time

-1

name

problem

scenario

optim

opset15

ERROR-msg

QuantileRegressor

m-reg

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

QuantileRegressor

~m-reg-64

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

QuantileRegressor

b-reg

default

OK 15/1

1.0.2

1

4

1

2.6e+02

1

0

skl2onnx

1.1

1

2.6e+02

1

0

-1

QuantileRegressor

m-reg

default

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

QuantileRegressor

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

QuantileRegressor

~m-reg-64

default

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

QuantileRegressor

b-reg

default

OK 15/1

0.24

0.26

0.26

0.3

0.22

0.14

0.26

0.25

0.26

0.25

0.27

0.29

0.32

0.21

0.22

QuantileRegressor

~b-reg-64

default

OK 13/

0.72

0.72

0.72

0.73

0.75

0.71

0.74

0.71

0.72

0.7

0.73

0.71

0.76

0.68

0.83

QuantileTransformer#

name

problem

scenario

optim

opset15

onx_nnodes

QuantileTransformer

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

QuantileTransformer

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

QuantileTransformer

num-tr

default

1.0.2

1

RANSAC#

name

problem

scenario

optim

opset15

onx_nnodes

RANSACRegressor

b-reg

default

OK 14/1

2

RANSACRegressor

m-reg

default

OK 14/1

2

RANSACRegressor

~b-reg-64

default

OK 14/

4

RANSACRegressor

~m-reg-64

default

OK 14/

4

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

RANSACRegressor

b-reg

default

OK 14/1

1.0.2

1

2.9e+02

2

0

skl2onnx

1.1

1

2.6e+02

1

0

-1

1

RANSACRegressor

m-reg

default

OK 14/1

1.0.2

1

3.4e+02

2

0

skl2onnx

1.1

1

3e+02

1

0

-1

1

RANSACRegressor

~b-reg-64

default

OK 14/

1.0.2

1

4e+02

4

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

1

RANSACRegressor

~m-reg-64

default

OK 14/

1.0.2

1

4.4e+02

4

3

skl2onnx

1.1

-1

4e+02

3

3

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

RANSACRegressor

b-reg

default

OK 14/1

0.18

0.18

0.19

0.23

0.13

0.18

0.2

0.18

0.2

0.18

0.21

0.21

0.25

0.098

0.17

RANSACRegressor

m-reg

default

OK 14/1

0.19

0.2

0.21

0.31

0.69

0.18

0.2

0.19

0.22

0.2

0.23

0.3

0.33

0.63

0.76

RANSACRegressor

~b-reg-64

default

OK 14/

0.47

0.47

0.47

0.5

0.66

0.46

0.48

0.46

0.5

0.45

0.52

0.46

0.55

0.54

0.81

RANSACRegressor

~m-reg-64

default

OK 14/

0.47

0.47

0.49

0.56

0.88

0.45

0.49

0.44

0.51

0.47

0.52

0.53

0.6

0.88

0.89

RBFSampler#

name

problem

scenario

optim

opset15

onx_nnodes

RBFSampler

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

RBFSampler

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

RBFSampler

num-tr

default

1.0.2

1

RFE#

name

problem

scenario

optim

opset15

onx_nnodes

RFE

num+y-tr

reg

OK 15/1

1

RFECV

num+y-tr

reg

OK 15/1

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

RFE

num+y-tr

reg

OK 15/1

1.0.2

1

2.4e+02

1

1

skl2onnx

1.1

1

2.4e+02

1

1

RFECV

num+y-tr

reg

OK 15/1

1.0.2

1

2.4e+02

1

1

skl2onnx

1.1

1

2.4e+02

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

RFE

num+y-tr

reg

OK 15/1

0.37

0.36

0.37

0.4

0.6

0.36

0.38

0.34

0.4

0.34

0.39

0.37

0.43

0.53

0.67

RFECV

num+y-tr

reg

OK 15/1

0.32

0.32

0.34

0.38

0.63

0.3

0.33

0.31

0.35

0.31

0.36

0.34

0.42

0.56

0.71

RandomizedSearch#

name

problem

scenario

optim

opset15

onx_nnodes

RandomizedSearchCV

b-cl

cl

RandomizedSearchCV

b-cl

reg

ERR: 2skl_meth

RandomizedSearchCV

m-cl

cl

RandomizedSearchCV

m-cl

reg

ERR: 2skl_meth

name

problem

scenario

optim

opset15

ERROR-msg

RandomizedSearchCV

b-cl

cl

NO CONVERTER

RandomizedSearchCV

b-cl

reg

ERR: 2skl_meth

‘LinearRegression’ object has no attribute ‘predict_proba’

RandomizedSearchCV

m-cl

cl

NO CONVERTER

RandomizedSearchCV

m-cl

reg

ERR: 2skl_meth

‘LinearRegression’ object has no attribute ‘predict_proba’

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

RandomizedSearchCV

b-cl

cl

1.0.2

1

RandomizedSearchCV

b-cl

reg

ERR: 2skl_meth

1.0.2

1

RandomizedSearchCV

m-cl

cl

1.0.2

1

RandomizedSearchCV

m-cl

reg

ERR: 2skl_meth

1.0.2

1

RegressorChain#

name

problem

scenario

optim

opset15

onx_nnodes

RegressorChain

b-reg

linreg

ERR: 1training_time

RegressorChain

m-reg

linreg

RegressorChain

~b-reg-64

linreg

ERR: 1training_time

RegressorChain

~m-reg-64

linreg

name

problem

scenario

optim

opset15

ERROR-msg

RegressorChain

b-reg

linreg

ERR: 1training_time

tuple index out of range

RegressorChain

m-reg

linreg

NO CONVERTER

RegressorChain

~b-reg-64

linreg

ERR: 1training_time

tuple index out of range

RegressorChain

~m-reg-64

linreg

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

RegressorChain

b-reg

linreg

ERR: 1training_time

1.0.2

-1

-1

-1

RegressorChain

m-reg

linreg

1.0.2

3

9

2

RegressorChain

~b-reg-64

linreg

ERR: 1training_time

1.0.2

-1

-1

-1

RegressorChain

~m-reg-64

linreg

1.0.2

3

9

2

SVM#

name

problem

scenario

optim

opset15

onx_nnodes

LinearSVC

~b-cl-nop

default

OK 15/1

2

LinearSVC

~b-cl-nop-64

default

-1

LinearSVR

b-reg

default

OK 15/1

1

LinearSVR

~b-reg-64

default

OK 13/

3

NuSVC

b-cl

prob

OK 9/1

4

NuSVC

m-cl

prob

OK 9/1

4

NuSVC

~b-cl-64

prob

OK 9/1

4

NuSVC

~b-cl-nan

prob

ERR: 1training_time

-1

NuSVR

b-reg

default

OK 9/1

2

NuSVR

~b-reg-64

default

OK 9/

2

OneClassSVM

outlier

default

OK 9/1

4

SGDOneClassSVM

outlier

default

SVC

b-cl

linear

{‘zipmap’: False}

OK 9/1

2

SVC

b-cl

poly

{‘zipmap’: False}

OK 9/1

2

SVC

b-cl

rbf

{‘zipmap’: False}

OK 9/1

2

SVC

b-cl

sigmoid

{‘zipmap’: False}

e<0.0001 9/1

2

SVC

m-cl

linear

{‘zipmap’: False}

e<0.001 9/1

2

SVC

m-cl

poly

{‘zipmap’: False}

e<0.001 9/1

2

SVC

m-cl

rbf

{‘zipmap’: False}

OK 9/1

2

SVC

m-cl

sigmoid

{‘zipmap’: False}

OK 9/1

2

SVC

~b-cl-64

linear

{‘zipmap’: False}

OK 9/

2

SVC

~b-cl-64

poly

{‘zipmap’: False}

OK 9/

2

SVC

~b-cl-64

rbf

{‘zipmap’: False}

OK 9/

2

SVC

~b-cl-64

sigmoid

{‘zipmap’: False}

OK 9/

2

SVC

~b-cl-nan

linear

ERR: 1training_time

-1

SVC

~b-cl-nan

poly

ERR: 1training_time

-1

SVC

~b-cl-nan

rbf

ERR: 1training_time

-1

SVC

~b-cl-nan

sigmoid

ERR: 1training_time

-1

SVR

b-reg

linear

e<0.0001 9/1

2

SVR

b-reg

poly

e<0.0001 9/1

2

SVR

b-reg

rbf

OK 9/1

2

SVR

b-reg

sigmoid

OK 9/1

2

SVR

~b-reg-64

linear

OK 9/

2

SVR

~b-reg-64

poly

OK 9/

2

SVR

~b-reg-64

rbf

OK 9/

2

SVR

~b-reg-64

sigmoid

OK 9/

2

name

problem

scenario

optim

opset15

ERROR-msg

LinearSVC

~b-cl-nop-64

default

post_transform ‘NONE’ is not supported with double.

NuSVC

~b-cl-nan

prob

ERR: 1training_time

Input contains NaN, infinity or a value too large for dtype(‘float64’).

SGDOneClassSVM

outlier

default

NO CONVERTER

SVC

~b-cl-nan

linear

ERR: 1training_time

Input contains NaN, infinity or a value too large for dtype(‘float64’).

SVC

~b-cl-nan

poly

ERR: 1training_time

Input contains NaN, infinity or a value too large for dtype(‘float64’).

SVC

~b-cl-nan

rbf

ERR: 1training_time

Input contains NaN, infinity or a value too large for dtype(‘float64’).

SVC

~b-cl-nan

sigmoid

ERR: 1training_time

Input contains NaN, infinity or a value too large for dtype(‘float64’).

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

LinearSVC

~b-cl-nop

default

OK 15/1

1.0.2

1

1

1

5.4e+02

2

1

skl2onnx

1.1

1

5.4e+02

2

1

LinearSVC

~b-cl-nop-64

default

1.0.2

1

3

1

-1

-1

-1

-1

-1

-1

-1

LinearSVR

b-reg

default

OK 15/1

1.0.2

1

4

1

2.5e+02

1

0

skl2onnx

1.1

1

2.5e+02

1

0

-1

LinearSVR

~b-reg-64

default

OK 13/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

-1

3.6e+02

3

3

1

NuSVC

b-cl

prob

OK 9/1

1.0.2

1

2e+03

4

0

skl2onnx

1.1

1

2e+03

4

0

2

-1

1

NuSVC

m-cl

prob

OK 9/1

1.0.2

1

3.2e+03

4

0

skl2onnx

1.1

1

3.2e+03

4

0

2

-1

1

NuSVC

~b-cl-64

prob

OK 9/1

1.0.2

1

2.1e+03

4

0

skl2onnx

1.1

1

2.1e+03

4

0

2

1

1

NuSVC

~b-cl-nan

prob

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

NuSVR

b-reg

default

OK 9/1

1.0.2

1

1.8e+03

2

0

skl2onnx

1.1

1

1.8e+03

2

0

1

-1

NuSVR

~b-reg-64

default

OK 9/

1.0.2

1

1.9e+03

2

0

skl2onnx

1.1

-1

1.9e+03

2

0

1

1

OneClassSVM

outlier

default

OK 9/1

1.0.2

1

1.9e+03

4

0

skl2onnx

1.1

1

1.9e+03

4

0

2

SGDOneClassSVM

outlier

default

1.0.2

1

4

1

SVC

b-cl

linear

{‘zipmap’: False}

OK 9/1

1.0.2

1

1

1

5.8e+02

2

0

skl2onnx

1.1

1

5.8e+02

2

0

1

-1

SVC

b-cl

poly

{‘zipmap’: False}

OK 9/1

1.0.2

1

-1

-1

5.8e+02

2

0

skl2onnx

1.1

1

5.8e+02

2

0

1

-1

SVC

b-cl

rbf

{‘zipmap’: False}

OK 9/1

1.0.2

1

-1

-1

8.3e+02

2

0

skl2onnx

1.1

1

8.3e+02

2

0

1

-1

SVC

b-cl

sigmoid

{‘zipmap’: False}

e<0.0001 9/1

1.0.2

1

-1

-1

2.2e+03

2

0

skl2onnx

1.1

1

2.2e+03

2

0

1

-1

SVC

m-cl

linear

{‘zipmap’: False}

e<0.001 9/1

1.0.2

1

3

1

1.5e+03

2

0

skl2onnx

1.1

1

1.5e+03

2

0

1

-1

SVC

m-cl

poly

{‘zipmap’: False}

e<0.001 9/1

1.0.2

1

-1

-1

1.3e+03

2

0

skl2onnx

1.1

1

1.3e+03

2

0

1

-1

SVC

m-cl

rbf

{‘zipmap’: False}

OK 9/1

1.0.2

1

-1

-1

2.3e+03

2

0

skl2onnx

1.1

1

2.3e+03

2

0

1

-1

SVC

m-cl

sigmoid

{‘zipmap’: False}

OK 9/1

1.0.2

1

-1

-1

3.9e+03

2

0

skl2onnx

1.1

1

3.9e+03

2

0

1

-1

SVC

~b-cl-64

linear

{‘zipmap’: False}

OK 9/

1.0.2

1

1

1

5.9e+02

2

0

skl2onnx

1.1

-1

5.9e+02

2

0

1

1

SVC

~b-cl-64

poly

{‘zipmap’: False}

OK 9/

1.0.2

1

-1

-1

5.8e+02

2

0

skl2onnx

1.1

-1

5.8e+02

2

0

1

1

SVC

~b-cl-64

rbf

{‘zipmap’: False}

OK 9/

1.0.2

1

-1

-1

8.6e+02

2

0

skl2onnx

1.1

-1

8.6e+02

2

0

1

1

SVC

~b-cl-64

sigmoid

{‘zipmap’: False}

OK 9/

1.0.2

1

-1

-1

2.2e+03

2

0

skl2onnx

1.1

-1

2.2e+03

2

0

1

1

SVC

~b-cl-nan

linear

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

SVC

~b-cl-nan

poly

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

SVC

~b-cl-nan

rbf

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

SVC

~b-cl-nan

sigmoid

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

SVR

b-reg

linear

e<0.0001 9/1

1.0.2

1

1

1

2.8e+03

2

0

skl2onnx

1.1

1

2.8e+03

2

0

1

-1

SVR

b-reg

poly

e<0.0001 9/1

1.0.2

1

-1

-1

2.8e+03

2

0

skl2onnx

1.1

1

2.8e+03

2

0

1

-1

SVR

b-reg

rbf

OK 9/1

1.0.2

1

-1

-1

2.6e+03

2

0

skl2onnx

1.1

1

2.6e+03

2

0

1

-1

SVR

b-reg

sigmoid

OK 9/1

1.0.2

1

-1

-1

2.7e+03

2

0

skl2onnx

1.1

1

2.7e+03

2

0

1

-1

SVR

~b-reg-64

linear

OK 9/

1.0.2

1

1

1

2.8e+03

2

0

skl2onnx

1.1

-1

2.8e+03

2

0

1

1

SVR

~b-reg-64

poly

OK 9/

1.0.2

1

-1

-1

2.9e+03

2

0

skl2onnx

1.1

-1

2.9e+03

2

0

1

1

SVR

~b-reg-64

rbf

OK 9/

1.0.2

1

-1

-1

2.6e+03

2

0

skl2onnx

1.1

-1

2.6e+03

2

0

1

1

SVR

~b-reg-64

sigmoid

OK 9/

1.0.2

1

-1

-1

2.7e+03

2

0

skl2onnx

1.1

-1

2.7e+03

2

0

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

LinearSVC

~b-cl-nop

default

OK 15/1

0.7

0.72

0.75

0.88

0.93

0.67

0.72

0.67

0.74

0.66

0.91

0.76

0.95

0.67

1.4

LinearSVR

b-reg

default

OK 15/1

0.27

0.26

0.26

0.3

0.22

0.26

0.27

0.26

0.26

0.25

0.27

0.29

0.33

0.21

0.23

LinearSVR

~b-reg-64

default

OK 13/

0.75

0.72

0.72

0.74

0.74

0.74

0.77

0.71

0.72

0.7

0.75

0.72

0.75

0.69

0.8

NuSVC

b-cl

prob

OK 9/1

0.26

0.33

0.094

0.065

0.061

0.25

0.27

0.32

0.35

0.092

0.1

0.064

0.065

0.061

0.061

NuSVC

m-cl

prob

OK 9/1

0.26

0.34

0.084

0.062

0.059

0.25

0.26

0.33

0.35

0.082

0.087

0.061

0.064

0.059

0.059

NuSVC

~b-cl-64

prob

OK 9/1

0.27

0.33

0.18

0.062

0.059

0.26

0.28

0.32

0.34

0.091

0.92

0.061

0.062

0.058

0.059

NuSVR

b-reg

default

OK 9/1

0.15

0.25

0.079

0.061

0.061

0.14

0.16

0.24

0.25

0.077

0.084

0.06

0.062

0.059

0.063

NuSVR

~b-reg-64

default

OK 9/

0.16

0.24

0.073

0.053

0.054

0.15

0.17

0.23

0.25

0.069

0.076

0.052

0.054

0.051

0.057

OneClassSVM

outlier

default

OK 9/1

0.21

0.29

0.12

0.074

0.069

0.2

0.25

0.27

0.3

0.1

0.29

0.073

0.074

0.069

0.069

SVC

b-cl

linear

{‘zipmap’: False}

OK 9/1

0.19

0.23

0.17

0.13

0.12

0.18

0.22

0.22

0.25

0.16

0.18

0.13

0.13

0.12

0.12

SVC

b-cl

poly

{‘zipmap’: False}

OK 9/1

0.19

0.23

0.18

0.12

0.11

0.18

0.2

0.2

0.26

0.15

0.34

0.12

0.12

0.11

0.11

SVC

b-cl

rbf

{‘zipmap’: False}

OK 9/1

0.19

0.26

0.12

0.087

0.078

0.19

0.2

0.24

0.27

0.12

0.14

0.082

0.091

0.078

0.078

SVC

b-cl

sigmoid

{‘zipmap’: False}

e<0.0001 9/1

0.22

0.42

0.12

0.11

0.11

0.21

0.23

0.4

0.43

0.11

0.13

0.11

0.11

0.11

0.11

SVC

m-cl

linear

{‘zipmap’: False}

e<0.001 9/1

0.19

0.25

0.13

0.081

0.075

0.18

0.2

0.25

0.27

0.12

0.13

0.08

0.083

0.075

0.076

SVC

m-cl

poly

{‘zipmap’: False}

e<0.001 9/1

0.19

0.25

0.13

0.084

0.088

0.18

0.2

0.24

0.27

0.12

0.14

0.084

0.085

0.078

0.097

SVC

m-cl

rbf

{‘zipmap’: False}

OK 9/1

0.21

0.31

0.087

0.066

0.064

0.2

0.22

0.3

0.32

0.085

0.09

0.066

0.067

0.064

0.064

SVC

m-cl

sigmoid

{‘zipmap’: False}

OK 9/1

0.24

0.48

0.12

0.1

0.1

0.23

0.25

0.46

0.49

0.12

0.12

0.1

0.1

0.1

0.1

SVC

~b-cl-64

linear

{‘zipmap’: False}

OK 9/

0.2

0.24

0.18

0.13

0.12

0.19

0.2

0.23

0.25

0.16

0.19

0.13

0.14

0.12

0.13

SVC

~b-cl-64

poly

{‘zipmap’: False}

OK 9/

0.2

0.24

0.18

0.12

0.11

0.19

0.21

0.23

0.26

0.17

0.19

0.12

0.12

0.11

0.11

SVC

~b-cl-64

rbf

{‘zipmap’: False}

OK 9/

0.2

0.27

0.13

0.084

0.079

0.19

0.21

0.25

0.28

0.12

0.14

0.083

0.085

0.077

0.08

SVC

~b-cl-64

sigmoid

{‘zipmap’: False}

OK 9/

0.23

0.43

0.13

0.11

0.11

0.22

0.24

0.41

0.44

0.13

0.14

0.11

0.11

0.11

0.11

SVR

b-reg

linear

e<0.0001 9/1

0.14

0.18

0.11

0.056

0.053

0.14

0.15

0.18

0.2

0.085

0.34

0.055

0.057

0.052

0.055

SVR

b-reg

poly

e<0.0001 9/1

0.15

0.21

0.092

0.066

0.062

0.14

0.16

0.2

0.23

0.088

0.1

0.065

0.066

0.062

0.063

SVR

b-reg

rbf

OK 9/1

0.16

0.28

0.074

0.066

0.059

0.16

0.17

0.27

0.29

0.072

0.08

0.06

0.076

0.059

0.059

SVR

b-reg

sigmoid

OK 9/1

0.18

0.41

0.12

0.1

0.1

0.18

0.19

0.4

0.42

0.11

0.12

0.1

0.1

0.1

0.1

SVR

~b-reg-64

linear

OK 9/

0.15

0.2

0.094

0.065

0.058

0.14

0.17

0.19

0.21

0.091

0.1

0.064

0.065

0.058

0.059

SVR

~b-reg-64

poly

OK 9/

0.15

0.22

0.091

0.063

0.059

0.15

0.16

0.21

0.23

0.088

0.11

0.062

0.064

0.059

0.059

SVR

~b-reg-64

rbf

OK 9/

0.17

0.27

0.069

0.057

0.052

0.16

0.18

0.26

0.28

0.067

0.076

0.054

0.067

0.052

0.053

SVR

~b-reg-64

sigmoid

OK 9/

0.19

0.42

0.13

0.1

0.1

0.18

0.2

0.4

0.43

0.11

0.24

0.1

0.1

0.1

0.1

Scaler#

name

problem

scenario

optim

opset15

onx_nnodes

MaxAbsScaler

num-tr

default

OK 15/1

1

MinMaxScaler

num-tr

default

OK 14/

3

Normalizer

num-tr

l1

OK 15/1

1

Normalizer

num-tr

l2

OK 15/1

1

Normalizer

num-tr

max

OK 15/1

1

RobustScaler

num-tr

default

OK 15/1

1

StandardScaler

num-tr

default

OK 15/1

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

MaxAbsScaler

num-tr

default

OK 15/1

1.0.2

1

2.4e+02

1

0

skl2onnx

1.1

1

2.4e+02

1

0

MinMaxScaler

num-tr

default

OK 14/

1.0.2

1

3.2e+02

3

2

skl2onnx

1.1

3.2e+02

3

2

1

Normalizer

num-tr

l1

OK 15/1

1.0.2

1

2e+02

1

0

skl2onnx

1.1

1

2e+02

1

0

Normalizer

num-tr

l2

OK 15/1

1.0.2

1

2e+02

1

0

skl2onnx

1.1

1

2e+02

1

0

Normalizer

num-tr

max

OK 15/1

1.0.2

1

2e+02

1

0

skl2onnx

1.1

1

2e+02

1

0

RobustScaler

num-tr

default

OK 15/1

1.0.2

1

2.4e+02

1

0

skl2onnx

1.1

1

2.4e+02

1

0

StandardScaler

num-tr

default

OK 15/1

1.0.2

1

2.4e+02

1

0

skl2onnx

1.1

1

2.4e+02

1

0

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

MaxAbsScaler

num-tr

default

OK 15/1

0.24

0.26

0.29

0.42

0.77

0.23

0.25

0.24

0.28

0.27

0.3

0.4

0.44

0.72

0.83

MinMaxScaler

num-tr

default

OK 14/

0.31

0.32

0.36

0.47

0.82

0.3

0.33

0.31

0.34

0.33

0.39

0.44

0.52

0.78

0.87

Normalizer

num-tr

l1

OK 15/1

0.19

0.2

0.22

0.35

0.65

0.18

0.2

0.18

0.21

0.21

0.24

0.33

0.37

0.63

0.67

Normalizer

num-tr

l2

OK 15/1

0.23

0.23

0.25

0.39

0.8

0.21

0.24

0.21

0.24

0.24

0.28

0.36

0.4

0.79

0.81

Normalizer

num-tr

max

OK 15/1

0.18

0.19

0.23

0.43

0.8

0.17

0.19

0.18

0.2

0.22

0.27

0.42

0.46

0.78

0.82

RobustScaler

num-tr

default

OK 15/1

0.22

0.23

0.24

0.26

0.27

0.21

0.24

0.22

0.24

0.21

0.26

0.24

0.29

0.26

0.28

StandardScaler

num-tr

default

OK 15/1

0.21

0.23

0.24

0.23

0.2

0.2

0.22

0.22

0.24

0.21

0.27

0.21

0.24

0.2

0.21

Select…#

name

problem

scenario

optim

opset15

onx_nnodes

SelectFdr

num+y-tr-cl

default

OK 15/1

1

SelectFpr

num+y-tr-cl

default

OK 15/1

1

SelectFromModel

num+y-tr

rf

OK 15/1

1

SelectFwe

num+y-tr-cl

alpha100

OK 15/1

1

SelectKBest

num+y-tr

k2

OK 15/1

1

SelectPercentile

num+y-tr

p50

OK 15/1

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

SelectFdr

num+y-tr-cl

default

OK 15/1

1.0.2

1

2.4e+02

1

1

skl2onnx

1.1

1

2.4e+02

1

1

SelectFpr

num+y-tr-cl

default

OK 15/1

1.0.2

1

2.4e+02

1

1

skl2onnx

1.1

1

2.4e+02

1

1

SelectFromModel

num+y-tr

rf

OK 15/1

1.0.2

1

2.5e+02

1

1

skl2onnx

1.1

1

2.5e+02

1

1

SelectFwe

num+y-tr-cl

alpha100

OK 15/1

1.0.2

1

2.4e+02

1

1

skl2onnx

1.1

1

2.4e+02

1

1

SelectKBest

num+y-tr

k2

OK 15/1

1.0.2

1

2.4e+02

1

1

skl2onnx

1.1

1

2.4e+02

1

1

SelectPercentile

num+y-tr

p50

OK 15/1

1.0.2

1

2.5e+02

1

1

skl2onnx

1.1

1

2.5e+02

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

SelectFdr

num+y-tr-cl

default

OK 15/1

0.28

0.27

0.28

0.31

0.59

0.27

0.29

0.26

0.3

0.26

0.31

0.29

0.33

0.51

0.67

SelectFpr

num+y-tr-cl

default

OK 15/1

0.38

0.38

0.39

0.43

0.72

0.36

0.4

0.36

0.39

0.36

0.42

0.4

0.46

0.64

0.79

SelectFromModel

num+y-tr

rf

OK 15/1

0.14

0.14

0.14

0.15

0.2

0.13

0.15

0.13

0.15

0.13

0.15

0.14

0.17

0.18

0.23

SelectFwe

num+y-tr-cl

alpha100

OK 15/1

0.37

0.37

0.38

0.42

0.71

0.35

0.39

0.35

0.39

0.35

0.43

0.38

0.44

0.62

0.81

SelectKBest

num+y-tr

k2

OK 15/1

0.3

0.3

0.3

0.32

0.49

0.28

0.32

0.28

0.32

0.27

0.32

0.29

0.34

0.39

0.62

SelectPercentile

num+y-tr

p50

OK 15/1

0.088

0.088

0.088

0.098

0.17

0.085

0.091

0.085

0.092

0.084

0.096

0.094

0.1

0.16

0.18

SelfTraining#

name

problem

scenario

optim

opset15

onx_nnodes

SelfTrainingClassifier

b-cl

default

?

SelfTrainingClassifier

m-cl

default

?

SelfTrainingClassifier

~b-cl-64

default

?

SelfTrainingClassifier

~m-label

default

?

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

SelfTrainingClassifier

b-cl

default

?

1.0.2

SelfTrainingClassifier

m-cl

default

?

1.0.2

SelfTrainingClassifier

~b-cl-64

default

?

1.0.2

SelfTrainingClassifier

~m-label

default

?

1.0.2

SequentialFeatureSelector#

name

problem

scenario

optim

opset15

onx_nnodes

SequentialFeatureSelector

num-tr

default

?

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

SequentialFeatureSelector

num-tr

default

?

1.0.2

SimpleImputer#

name

problem

scenario

optim

opset15

onx_nnodes

SimpleImputer

num-tr

default

OK 15/1

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

SimpleImputer

num-tr

default

OK 15/1

1.0.2

1

2.6e+02

1

0

skl2onnx

1.1

1

2.6e+02

1

0

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

SimpleImputer

num-tr

default

OK 15/1

0.39

0.39

0.38

0.38

0.33

0.37

0.39

0.37

0.4

0.35

0.41

0.36

0.42

0.31

0.36

SkewedChi2Sampler#

name

problem

scenario

optim

opset15

onx_nnodes

SkewedChi2Sampler

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

SkewedChi2Sampler

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

SkewedChi2Sampler

num-tr

default

1.0.2

1

Sparse…#

name

problem

scenario

optim

opset15

onx_nnodes

SparseCoder

ERR: 0problem

SparsePCA

num-tr

default

SparseRandomProjection

num-tr

eps95

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

SparseCoder

ERR: 0problem

SKIPPED

SparsePCA

num-tr

default

NO CONVERTER

SparseRandomProjection

num-tr

eps95

ERR: 1training_time

eps=0.950000 and n_samples=112 lead to a target dimension of 114 which is l…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

SparseCoder

ERR: 0problem

1.0.2

SparsePCA

num-tr

default

1.0.2

1

SparseRandomProjection

num-tr

eps95

ERR: 1training_time

1.0.2

SplineTransformer#

name

problem

scenario

optim

opset15

onx_nnodes

SplineTransformer

num-tr

default

name

problem

scenario

optim

opset15

ERROR-msg

SplineTransformer

num-tr

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

SplineTransformer

num-tr

default

1.0.2

1

Stacking#

name

problem

scenario

optim

opset15

onx_nnodes

StackingClassifier

b-cl

logreg

{‘zipmap’: False}

OK 14/1

17

StackingRegressor

b-reg

linreg

OK 14/1

8

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

StackingClassifier

b-cl

logreg

{‘zipmap’: False}

OK 14/1

1.0.2

3

2

2

2.2e+03

17

3

skl2onnx

1.1

1

2.1e+03

16

3

1

4

1

StackingRegressor

b-reg

linreg

OK 14/1

1.0.2

3

8

2

8.4e+02

8

0

skl2onnx

1.1

1

7.8e+02

7

0

3

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

StackingClassifier

b-cl

logreg

{‘zipmap’: False}

OK 14/1

0.85

0.92

0.95

1.4

2.4

0.81

0.89

0.86

0.95

0.83

1

1.4

1.5

2.4

2.4

StackingRegressor

b-reg

linreg

OK 14/1

0.28

0.29

0.29

0.33

0.41

0.27

0.29

0.27

0.3

0.28

0.31

0.31

0.34

0.39

0.43

Tfidf…#

name

problem

scenario

optim

opset15

onx_nnodes

TfidfTransformer

CRASH

TfidfVectorizer

text-col

default

OK 14/1

8

name

problem

scenario

optim

opset15

ERROR-msg

TfidfTransformer

CRASH

Unable to find ‘./bench_python_compiled/bench_sum_python_compiled_TfidfTran…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

TfidfTransformer

CRASH

TfidfVectorizer

text-col

default

OK 14/1

1.0.2

1

1.3e+03

8

2

skl2onnx

1.1

1

1.2e+03

7

2

1

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

TfidfVectorizer

text-col

default

OK 14/1

0.23

0.44

1.2

1.8

1.9

0.23

0.24

0.44

0.46

1.2

1.2

1.8

1.8

1.9

1.9

TransferTransformer#

name

problem

scenario

optim

opset15

onx_nnodes

TransferTransformer

num-tr

default

?

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

TransferTransformer

num-tr

default

?

1.0.2

TransformedTarget#

name

problem

scenario

optim

opset15

onx_nnodes

TransformedTargetRegressor

b-reg

default

TransformedTargetRegressor

m-reg

default

TransformedTargetRegressor

~b-reg-64

default

TransformedTargetRegressor

~m-reg-64

default

name

problem

scenario

optim

opset15

ERROR-msg

TransformedTargetRegressor

b-reg

default

NO CONVERTER

TransformedTargetRegressor

m-reg

default

NO CONVERTER

TransformedTargetRegressor

~b-reg-64

default

NO CONVERTER

TransformedTargetRegressor

~m-reg-64

default

NO CONVERTER

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

TransformedTargetRegressor

b-reg

default

1.0.2

TransformedTargetRegressor

m-reg

default

1.0.2

TransformedTargetRegressor

~b-reg-64

default

1.0.2

TransformedTargetRegressor

~m-reg-64

default

1.0.2

Trees#

name

problem

scenario

optim

opset15

onx_nnodes

DecisionTreeClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1

DecisionTreeClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1

DecisionTreeClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1

DecisionTreeClassifier

~b-cl-f100

default

{‘zipmap’: False}

OK 15/1

1

DecisionTreeClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

23

DecisionTreeRegressor

b-reg

default

OK 15/1

1

DecisionTreeRegressor

m-reg

default

OK 15/1

1

DecisionTreeRegressor

~b-reg-64

default

OK 15/

1

DecisionTreeRegressor

~b-reg-f100

default

OK 15/1

1

DecisionTreeRegressor

~m-reg-64

default

OK 15/

1

ExtraTreeClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1

ExtraTreeClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1

ExtraTreeClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1

ExtraTreeClassifier

~b-cl-f100

default

{‘zipmap’: False}

OK 15/1

1

ExtraTreeClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

23

ExtraTreeRegressor

b-reg

default

OK 15/1

1

ExtraTreeRegressor

m-reg

default

OK 15/1

1

ExtraTreeRegressor

~b-reg-64

default

OK 15/

1

ExtraTreeRegressor

~m-reg-64

default

OK 15/

1

ExtraTreesClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1

ExtraTreesClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1

ExtraTreesClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1

ExtraTreesClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

89

ExtraTreesRegressor

b-reg

default

OK 15/1

1

ExtraTreesRegressor

m-reg

default

OK 15/1

1

ExtraTreesRegressor

~b-reg-64

default

OK 15/

1

ExtraTreesRegressor

~m-reg-64

default

OK 15/

1

IsolationForest

outlier

default

OK 15/2

2.8e+02

IsolationForest

outlier

default

OK 15/2

2.8e+02

LGBMClassifier

b-cl

default

{‘zipmap’: False}

OK 14/1

3

LGBMClassifier

m-cl

default

{‘zipmap’: False}

OK 14/1

3

LGBMClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 14/

3

LGBMRegressor

b-reg

default

OK 14/1

2

LGBMRegressor

~b-reg-64

default

OK 14/

2

RandomForestClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1

RandomForestClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1

RandomForestClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1

RandomForestClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

89

RandomForestRegressor

b-reg

default

OK 15/1

1

RandomForestRegressor

m-reg

default

OK 15/1

1

RandomForestRegressor

~b-reg-64

default

OK 15/

1

RandomForestRegressor

~m-reg-64

default

OK 15/

1

RandomTreesEmbedding

num-tr

default

XGBClassifier

b-cl

default

-1

XGBClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1

XGBClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1

XGBClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/1

1

XGBRegressor

b-reg

default

OK 15/1

1

XGBRegressor

~b-reg-64

default

OK 15/

1

name

problem

scenario

optim

opset15

ERROR-msg

RandomTreesEmbedding

num-tr

default

The converter cannot convert the model with sparse outputs.

XGBClassifier

b-cl

default

The model is using version 3 of domain ‘ai.onnx.ml’ not supported yet by th…

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

DecisionTreeClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

7e+02

1

0

skl2onnx

1.1

1

7e+02

1

0

-1

3

1

1

-1

-1

DecisionTreeClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1.6e+03

1

0

skl2onnx

1.1

1

1.6e+03

1

0

-1

21

1

6

-1

-1

DecisionTreeClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1.0.2

1

8.1e+02

1

0

skl2onnx

1.1

-1

8.1e+02

1

0

-1

3

1

1

-1

1

DecisionTreeClassifier

~b-cl-f100

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

7e+02

1

0

skl2onnx

1.1

1

7e+02

1

0

-1

3

1

1

-1

-1

DecisionTreeClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

6.4e+03

23

7

skl2onnx

1.1

1

6.4e+03

23

7

7

63

1

9

2

-1

DecisionTreeRegressor

b-reg

default

OK 15/1

1.0.2

1

8.9e+03

1

0

skl2onnx

1.1

1

8.9e+03

1

0

2.2e+02

1

13

-1

DecisionTreeRegressor

m-reg

default

OK 15/1

1.0.2

1

1e+04

1

0

skl2onnx

1.1

1

1e+04

1

0

2.2e+02

1

13

-1

DecisionTreeRegressor

~b-reg-64

default

OK 15/

1.0.2

1

1.1e+04

1

0

skl2onnx

1.1

-1

1.1e+04

1

0

2.2e+02

1

13

1

DecisionTreeRegressor

~b-reg-f100

default

OK 15/1

1.0.2

1

8.9e+03

1

0

skl2onnx

1.1

1

8.9e+03

1

0

2.2e+02

1

11

-1

DecisionTreeRegressor

~m-reg-64

default

OK 15/

1.0.2

1

1.2e+04

1

0

skl2onnx

1.1

-1

1.2e+04

1

0

2.2e+02

1

13

1

ExtraTreeClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1.4e+03

1

0

skl2onnx

1.1

1

1.4e+03

1

0

-1

23

1

8

-1

-1

ExtraTreeClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

4.5e+03

1

0

skl2onnx

1.1

1

4.5e+03

1

0

-1

81

1

14

-1

-1

ExtraTreeClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1.0.2

1

1.7e+03

1

0

skl2onnx

1.1

-1

1.7e+03

1

0

-1

23

1

8

-1

1

ExtraTreeClassifier

~b-cl-f100

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

7.8e+02

1

0

skl2onnx

1.1

1

7.8e+02

1

0

-1

5

1

2

-1

-1

ExtraTreeClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1e+04

23

7

skl2onnx

1.1

1

1e+04

23

7

7

1.3e+02

1

13

2

-1

ExtraTreeRegressor

b-reg

default

OK 15/1

1.0.2

1

8.9e+03

1

0

skl2onnx

1.1

1

8.9e+03

1

0

2.2e+02

1

14

-1

ExtraTreeRegressor

m-reg

default

OK 15/1

1.0.2

1

1e+04

1

0

skl2onnx

1.1

1

1e+04

1

0

2.2e+02

1

14

-1

ExtraTreeRegressor

~b-reg-64

default

OK 15/

1.0.2

1

1.1e+04

1

0

skl2onnx

1.1

-1

1.1e+04

1

0

2.2e+02

1

14

1

ExtraTreeRegressor

~m-reg-64

default

OK 15/

1.0.2

1

1.2e+04

1

0

skl2onnx

1.1

-1

1.2e+04

1

0

2.2e+02

1

14

1

ExtraTreesClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

6.9e+03

1

0

skl2onnx

1.1

1

6.9e+03

1

0

-1

1.7e+02

10

8

-1

-1

ExtraTreesClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

3.1e+04

1

0

skl2onnx

1.1

1

3.1e+04

1

0

-1

6.5e+02

10

16

-1

-1

ExtraTreesClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1.0.2

11

6.9e+03

1

0

skl2onnx

1.1

-1

6.9e+03

1

0

-1

1.7e+02

10

8

-1

1

ExtraTreesClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

9.2e+04

89

17

skl2onnx

1.1

1

9.2e+04

89

17

26

1.3e+03

10

18

20

-1

ExtraTreesRegressor

b-reg

default

OK 15/1

1.0.2

11

8.4e+04

1

0

skl2onnx

1.1

1

8.4e+04

1

0

2.2e+03

10

15

-1

ExtraTreesRegressor

m-reg

default

OK 15/1

1.0.2

11

9.7e+04

1

0

skl2onnx

1.1

1

9.7e+04

1

0

2.2e+03

10

15

-1

ExtraTreesRegressor

~b-reg-64

default

OK 15/

1.0.2

11

1e+05

1

0

skl2onnx

1.1

-1

1e+05

1

0

2.2e+03

10

15

1

ExtraTreesRegressor

~m-reg-64

default

OK 15/

1.0.2

11

1.2e+05

1

0

skl2onnx

1.1

-1

1.2e+05

1

0

2.2e+03

10

15

1

IsolationForest

outlier

default

OK 15/2

1.0.2

11

6.2e+04

2.8e+02

12

skl2onnx

1.1

2

6e+04

2.6e+02

12

20

8.2e+02

10

7

41

IsolationForest

outlier

default

OK 15/2

1.0.2

11

6.2e+04

2.8e+02

12

skl2onnx

1.1

2

6e+04

2.6e+02

12

20

8.2e+02

10

7

41

LGBMClassifier

b-cl

default

{‘zipmap’: False}

OK 14/1

1.0.2

1

1.5e+03

3

0

skl2onnx

1.1

1

1.4e+03

1

0

-1

2

LGBMClassifier

m-cl

default

{‘zipmap’: False}

OK 14/1

1.0.2

1

4.1e+03

3

0

skl2onnx

1.1

1

4e+03

1

0

-1

2

LGBMClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 14/

1.0.2

1

1.6e+03

3

0

skl2onnx

1.1

-1

1.4e+03

1

0

1

2

LGBMRegressor

b-reg

default

OK 14/1

1.0.2

1

2.8e+04

2

0

skl2onnx

1.1

1

2.8e+04

1

0

-1

1

LGBMRegressor

~b-reg-64

default

OK 14/

1.0.2

1

2.8e+04

2

0

skl2onnx

1.1

-1

2.8e+04

1

0

1

1

RandomForestClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

3.3e+03

1

0

skl2onnx

1.1

1

3.3e+03

1

0

-1

74

10

5

-1

-1

RandomForestClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

1.1e+04

1

0

skl2onnx

1.1

1

1.1e+04

1

0

-1

2.2e+02

10

8

-1

-1

RandomForestClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

1.0.2

11

3.3e+03

1

0

skl2onnx

1.1

-1

3.3e+03

1

0

-1

74

10

5

-1

1

RandomForestClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

1.0.2

11

4.4e+04

89

17

skl2onnx

1.1

1

4.4e+04

89

17

26

5.3e+02

10

10

20

-1

RandomForestRegressor

b-reg

default

OK 15/1

1.0.2

11

5.2e+04

1

0

skl2onnx

1.1

1

5.2e+04

1

0

1.4e+03

10

14

-1

RandomForestRegressor

m-reg

default

OK 15/1

1.0.2

11

5.9e+04

1

0

skl2onnx

1.1

1

5.9e+04

1

0

1.4e+03

10

14

-1

RandomForestRegressor

~b-reg-64

default

OK 15/

1.0.2

11

6.2e+04

1

0

skl2onnx

1.1

-1

6.2e+04

1

0

1.4e+03

10

14

1

RandomForestRegressor

~m-reg-64

default

OK 15/

1.0.2

11

7.2e+04

1

0

skl2onnx

1.1

-1

7.2e+04

1

0

1.4e+03

10

14

1

RandomTreesEmbedding

num-tr

default

1.0.2

1e+02

4.1e+03

1e+02

5

XGBClassifier

b-cl

default

1.0.2

1

-1

-1

-1

-1

-1

-1

-1

XGBClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1e+03

1

0

skl2onnx

1.1

1

1e+03

1

0

XGBClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

5.7e+03

1

0

skl2onnx

1.1

1

5.7e+03

1

0

XGBClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/1

1.0.2

1

1.1e+03

1

0

skl2onnx

1.1

1

1.1e+03

1

0

XGBRegressor

b-reg

default

OK 15/1

1.0.2

1

8.2e+04

1

0

skl2onnx

1.1

1

8.2e+04

1

0

-1

XGBRegressor

~b-reg-64

default

OK 15/

1.0.2

1

8.2e+04

1

0

skl2onnx

1.1

-1

8.2e+04

1

0

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

DecisionTreeClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.16

0.16

0.22

0.52

1

0.15

0.17

0.15

0.17

0.2

0.26

0.49

0.53

1

1

DecisionTreeClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.16

0.16

0.28

0.78

1.5

0.15

0.19

0.15

0.19

0.24

0.31

0.75

0.83

1.5

1.6

DecisionTreeClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

0.15

0.15

0.21

0.43

0.79

0.14

0.16

0.14

0.17

0.2

0.23

0.39

0.46

0.78

0.8

DecisionTreeClassifier

~b-cl-f100

default

{‘zipmap’: False}

OK 15/1

0.16

0.16

0.25

0.49

0.72

0.15

0.19

0.15

0.17

0.19

0.39

0.43

0.6

0.71

0.73

DecisionTreeClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

3.9

3.6

3.3

2.2

1.2

3.8

4

3.4

3.7

3.1

3.4

2.1

2.3

1.2

1.2

DecisionTreeRegressor

b-reg

default

OK 15/1

0.17

0.17

0.23

0.33

0.51

0.15

0.18

0.16

0.2

0.19

0.35

0.32

0.35

0.5

0.52

DecisionTreeRegressor

m-reg

default

OK 15/1

0.2

0.21

0.3

0.7

1.3

0.19

0.21

0.2

0.24

0.28

0.32

0.66

0.74

1.2

1.3

DecisionTreeRegressor

~b-reg-64

default

OK 15/

0.16

0.17

0.2

0.32

0.45

0.15

0.17

0.16

0.2

0.18

0.24

0.3

0.35

0.44

0.46

DecisionTreeRegressor

~b-reg-f100

default

OK 15/1

0.17

0.17

0.22

0.29

0.42

0.16

0.18

0.17

0.19

0.2

0.24

0.25

0.33

0.41

0.42

DecisionTreeRegressor

~m-reg-64

default

OK 15/

0.2

0.21

0.3

0.68

1.2

0.19

0.21

0.2

0.22

0.26

0.35

0.66

0.71

1.2

1.2

ExtraTreeClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.16

0.16

0.21

0.42

0.77

0.15

0.17

0.15

0.18

0.2

0.25

0.4

0.44

0.75

0.78

ExtraTreeClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.16

0.16

0.27

0.72

1.3

0.15

0.17

0.16

0.18

0.25

0.29

0.69

0.75

1.3

1.3

ExtraTreeClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

0.15

0.15

0.21

0.41

0.71

0.14

0.16

0.14

0.17

0.19

0.23

0.39

0.43

0.7

0.71

ExtraTreeClassifier

~b-cl-f100

default

{‘zipmap’: False}

OK 15/1

0.16

0.16

0.21

0.38

0.59

0.15

0.17

0.15

0.18

0.19

0.23

0.36

0.42

0.58

0.6

ExtraTreeClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

3.9

3.6

3.3

2.3

1.4

3.8

4

3.5

3.7

3.1

3.5

2.2

2.5

1.3

1.4

ExtraTreeRegressor

b-reg

default

OK 15/1

0.17

0.17

0.22

0.33

0.49

0.16

0.17

0.17

0.2

0.2

0.27

0.31

0.35

0.48

0.51

ExtraTreeRegressor

m-reg

default

OK 15/1

0.2

0.21

0.3

0.7

1.3

0.19

0.21

0.2

0.24

0.28

0.35

0.67

0.72

1.2

1.3

ExtraTreeRegressor

~b-reg-64

default

OK 15/

0.16

0.16

0.21

0.33

0.48

0.15

0.18

0.16

0.19

0.19

0.22

0.29

0.36

0.46

0.49

ExtraTreeRegressor

~m-reg-64

default

OK 15/

0.2

0.2

0.31

0.64

1.1

0.19

0.21

0.19

0.23

0.26

0.59

0.6

0.67

1.1

1.1

ExtraTreesClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.003

0.0035

0.0081

0.041

0.33

0.0029

0.0032

0.0033

0.0039

0.0078

0.0086

0.041

0.042

0.33

0.33

ExtraTreesClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.0031

0.0042

0.011

0.061

0.48

0.003

0.0033

0.0041

0.0044

0.01

0.012

0.06

0.061

0.46

0.5

ExtraTreesClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

0.003

0.0036

0.0081

0.04

0.31

0.0029

0.0032

0.0034

0.0038

0.0078

0.0086

0.039

0.041

0.3

0.31

ExtraTreesClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

0.3

0.3

0.31

0.48

1.7

0.29

0.31

0.28

0.31

0.3

0.33

0.4

0.7

1.7

1.7

ExtraTreesRegressor

b-reg

default

OK 15/1

0.0027

0.0038

0.0076

0.044

0.37

0.0026

0.003

0.0037

0.0042

0.0072

0.0085

0.043

0.044

0.36

0.37

ExtraTreesRegressor

m-reg

default

OK 15/1

0.0032

0.0046

0.012

0.076

0.66

0.0031

0.0035

0.0044

0.0049

0.011

0.013

0.074

0.078

0.64

0.68

ExtraTreesRegressor

~b-reg-64

default

OK 15/

0.0027

0.0037

0.0068

0.036

0.28

0.0026

0.0029

0.0036

0.0041

0.0063

0.0082

0.035

0.037

0.28

0.28

ExtraTreesRegressor

~m-reg-64

default

OK 15/

0.0032

0.0045

0.012

0.079

0.64

0.0031

0.0035

0.0044

0.005

0.011

0.013

0.077

0.08

0.64

0.64

IsolationForest

outlier

default

OK 15/2

0.38

0.4

0.59

1.9

5.1

0.37

0.39

0.39

0.4

0.59

0.59

1.9

1.9

5

5.1

IsolationForest

outlier

default

OK 15/2

0.38

0.39

0.59

1.9

5.3

0.37

0.39

0.38

0.4

0.58

0.59

1.9

1.9

5.1

5.5

LGBMClassifier

b-cl

default

{‘zipmap’: False}

OK 14/1

0.11

0.12

0.22

0.93

3.3

0.097

0.12

0.11

0.14

0.19

0.23

0.88

0.97

3.2

3.3

LGBMClassifier

m-cl

default

{‘zipmap’: False}

OK 14/1

0.14

0.16

0.35

1.8

4.4

0.13

0.15

0.15

0.17

0.21

0.42

1.8

1.9

4.3

4.5

LGBMClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 14/

0.11

0.12

0.2

0.71

2.4

0.11

0.12

0.1

0.13

0.18

0.23

0.68

0.75

2.3

2.4

LGBMRegressor

b-reg

default

OK 14/1

0.11

0.19

1.1

3.6

4.8

0.11

0.12

0.14

0.21

1

1.2

3.5

3.6

4.8

4.8

LGBMRegressor

~b-reg-64

default

OK 14/

0.11

0.19

1.1

3.5

4.6

0.1

0.12

0.18

0.21

1

1.1

3.4

3.5

4.5

4.6

RandomForestClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.003

0.0035

0.0086

0.049

0.36

0.003

0.0033

0.0034

0.0037

0.0081

0.0096

0.045

0.063

0.36

0.37

RandomForestClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.0031

0.0039

0.015

0.093

0.76

0.003

0.0033

0.0038

0.0043

0.014

0.015

0.091

0.095

0.75

0.77

RandomForestClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/

0.003

0.0034

0.0079

0.039

0.3

0.0029

0.0032

0.0033

0.0039

0.0077

0.0086

0.038

0.04

0.3

0.31

RandomForestClassifier

~m-label

default

{‘zipmap’: False}

OK 15/1

0.3

0.3

0.3

0.36

1.1

0.29

0.31

0.29

0.31

0.29

0.31

0.35

0.36

1.1

1.1

RandomForestRegressor

b-reg

default

OK 15/1

0.0026

0.0035

0.0073

0.042

0.35

0.0026

0.0029

0.0034

0.004

0.0068

0.0081

0.041

0.043

0.34

0.35

RandomForestRegressor

m-reg

default

OK 15/1

0.0031

0.0042

0.011

0.074

0.62

0.003

0.0033

0.004

0.0046

0.011

0.012

0.069

0.082

0.61

0.62

RandomForestRegressor

~b-reg-64

default

OK 15/

0.0026

0.0035

0.0057

0.029

0.22

0.0025

0.003

0.0033

0.0054

0.0054

0.0062

0.028

0.03

0.22

0.22

RandomForestRegressor

~m-reg-64

default

OK 15/

0.003

0.0041

0.01

0.066

0.55

0.0029

0.0032

0.004

0.0045

0.0093

0.011

0.065

0.067

0.54

0.56

XGBClassifier

b-cl

default

{‘zipmap’: False}

OK 15/1

0.0051

0.0055

0.013

0.078

0.63

0.0044

0.0055

0.0045

0.0063

0.013

0.014

0.076

0.079

0.63

0.63

XGBClassifier

m-cl

default

{‘zipmap’: False}

OK 15/1

0.0053

0.0067

0.022

0.13

0.89

0.0044

0.0057

0.0055

0.0074

0.021

0.022

0.095

0.16

0.69

1.3

XGBClassifier

~b-cl-64

default

{‘zipmap’: False}

OK 15/1

0.0051

0.0055

0.0096

0.051

0.39

0.0046

0.0055

0.0045

0.0064

0.0064

0.011

0.05

0.051

0.38

0.4

XGBRegressor

b-reg

default

OK 15/1

0.0063

0.013

0.073

0.56

3

0.004

0.026

0.01

0.015

0.054

0.11

0.44

0.62

2.5

3.7

XGBRegressor

~b-reg-64

default

OK 15/

0.0052

0.013

0.046

0.35

2.3

0.0046

0.0056

0.01

0.014

0.041

0.076

0.3

0.37

2.3

2.3

TruncatedSVD#

name

problem

scenario

optim

opset15

onx_nnodes

TruncatedSVD

num-tr

default

OK 13/

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

TruncatedSVD

num-tr

default

OK 13/

1.0.2

1

2.4e+02

1

1

skl2onnx

1.1

2.4e+02

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

TruncatedSVD

num-tr

default

OK 13/

0.22

0.23

0.24

0.34

0.66

0.21

0.23

0.22

0.26

0.23

0.26

0.32

0.36

0.61

0.71

Tweedie#

name

problem

scenario

optim

opset15

onx_nnodes

TweedieRegressor

b-reg

default

OK 15/

3

TweedieRegressor

m-reg

default

ERR: 1training_time

-1

TweedieRegressor

~b-reg-64

default

OK 15/

3

TweedieRegressor

~m-reg-64

default

ERR: 1training_time

-1

name

problem

scenario

optim

opset15

ERROR-msg

TweedieRegressor

m-reg

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

TweedieRegressor

~m-reg-64

default

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

TweedieRegressor

b-reg

default

OK 15/

1.0.2

1

4

1

3.6e+02

3

3

skl2onnx

1.1

3.6e+02

3

3

1

TweedieRegressor

m-reg

default

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

TweedieRegressor

~b-reg-64

default

OK 15/

1.0.2

1

4

1

3.8e+02

3

3

skl2onnx

1.1

3.8e+02

3

3

1

TweedieRegressor

~m-reg-64

default

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

TweedieRegressor

b-reg

default

OK 15/

0.64

0.68

0.68

0.65

0.4

0.6

0.65

0.66

0.71

0.6

0.75

0.61

0.72

0.35

0.45

TweedieRegressor

~b-reg-64

default

OK 15/

0.66

0.7

0.71

0.71

0.77

0.64

0.68

0.67

0.74

0.6

0.75

0.68

0.79

0.62

0.95

VarianceThreshold#

name

problem

scenario

optim

opset15

onx_nnodes

VarianceThreshold

num-tr

default

OK 15/1

1

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

VarianceThreshold

num-tr

default

OK 15/1

1.0.2

1

2.5e+02

1

1

skl2onnx

1.1

1

2.5e+02

1

1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

VarianceThreshold

num-tr

default

OK 15/1

0.43

0.42

0.44

0.49

0.87

0.41

0.44

0.4

0.46

0.42

0.48

0.44

0.53

0.73

1

Voting#

name

problem

scenario

optim

opset15

onx_nnodes

VotingClassifier

b-cl

logreg-noflatten

{‘zipmap’: False}

OK 15/1

12

VotingClassifier

m-cl

logreg-noflatten

{‘zipmap’: False}

OK 15/1

12

VotingRegressor

b-reg

linreg

OK 15/1

7

VotingRegressor

m-reg

linreg

ERR: 1training_time

-1

VotingRegressor

~b-reg-64

linreg

-1

VotingRegressor

~m-reg-64

linreg

ERR: 1training_time

-1

name

problem

scenario

optim

opset15

ERROR-msg

VotingRegressor

m-reg

linreg

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

VotingRegressor

~b-reg-64

linreg

‘float’ object has no attribute ‘reshape’

VotingRegressor

~m-reg-64

linreg

ERR: 1training_time

y should be a 1d array, got an array of shape (112, 2) instead.

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

VotingClassifier

b-cl

logreg-noflatten

{‘zipmap’: False}

OK 15/1

1.0.2

3

2

2

1.4e+03

12

4

skl2onnx

1.1

1

1.4e+03

12

3

1

2

VotingClassifier

m-cl

logreg-noflatten

{‘zipmap’: False}

OK 15/1

1.0.2

3

6

2

1.5e+03

12

4

skl2onnx

1.1

1

1.5e+03

12

3

1

2

VotingRegressor

b-reg

linreg

OK 15/1

1.0.2

3

8

2

5.6e+02

7

1

skl2onnx

1.1

1

5.6e+02

7

1

VotingRegressor

m-reg

linreg

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

VotingRegressor

~b-reg-64

linreg

1.0.2

3

8

2

-1

-1

-1

-1

-1

-1

-1

VotingRegressor

~m-reg-64

linreg

ERR: 1training_time

1.0.2

-1

-1

-1

-1

-1

-1

-1

-1

-1

-1

name

problem

scenario

optim

opset15

RT/SKL-N=1

N=10

N=100

N=1000

N=10000

RT/SKL-N=1-min

RT/SKL-N=1-max

N=10-min

N=10-max

N=100-min

N=100-max

N=1000-min

N=1000-max

N=10000-min

N=10000-max

VotingClassifier

b-cl

logreg-noflatten

{‘zipmap’: False}

OK 15/1

0.65

0.73

0.78

1.2

1.9

0.4

0.74

0.67

0.79

0.72

0.83

1.1

1.2

1.9

1.9

VotingClassifier

m-cl

logreg-noflatten

{‘zipmap’: False}

OK 15/1

0.7

0.76

0.77

0.87

0.9

0.42

0.79

0.7

0.79

0.72

0.81

0.83

0.91

0.9

0.9

VotingRegressor

b-reg

linreg

OK 15/1

0.56

0.57

0.58

0.6

0.57

0.33

0.61

0.55

0.59

0.52

0.6

0.55

0.64

0.53

0.61

WOETransformer#

name

problem

scenario

optim

opset15

onx_nnodes

WOETransformer

num-tr

default

ERR: 1training_time

name

problem

scenario

optim

opset15

ERROR-msg

WOETransformer

num-tr

default

ERR: 1training_time

object of type ‘NoneType’ has no len()

name

problem

scenario

optim

opset15

skl_version

skl_nop

skl_ncoef

skl_nlin

onx_size

onx_nnodes

onx_ninits

onx_producer_name

onx_producer_version

onx_ai.onnx.ml

onx_size_optim

onx_nnodes_optim

onx_ninits_optim

onx_op_Reshape

skl_nnodes

skl_ntrees

skl_max_depth

onx_op_Cast

onx_mlprodict

onx_op_ZipMap

onx_com.microsoft

onx_op_Identity

onx_op_Identity_optim

onx_subgraphs

onx_subgraphs_optim

WOETransformer

num-tr

default

ERR: 1training_time

1.0.2

previous

ExtraTreeRegressor - ~m-reg-64 - default -

next

Availability of scikit-learn model for runtime onnxruntime1