MultiOutputRegressor - m-reg - linreg -#

Fitted on a problem type m-reg (see find_suitable_problem), method predict matches output .

MultiOutputRegressor(estimator=LinearRegression(), n_jobs=8)

index

0

skl_nop

3

skl_ncoef

8

skl_nlin

2

onx_size

665

onx_nnodes

5

onx_ninits

1

onx_doc_string

onx_ir_version

8

onx_domain

ai.onnx

onx_model_version

0

onx_producer_name

skl2onnx

onx_producer_version

1.11.1

onx_

15

onx_ai.onnx.ml

1

onx_op_Reshape

2

onx_size_optim

665

onx_nnodes_optim

5

onx_ninits_optim

1

fit_estimators_.size

2

fit_estimators_.singular_.shape

4

fit_estimators_.coef_.shape

4

%0 X X float((0, 4)) LinearRegressor LinearRegressor (LinearRegressor) coefficients=[-0.19476996  0.04... intercepts=[0.17583406] X->LinearRegressor LinearRegressor1 LinearRegressor (LinearRegressor1) coefficients=[-0.19476973  0.04... intercepts=[0.67583275] X->LinearRegressor1 variable variable float((0, 2)) Re_Reshapecst Re_Reshapecst int64((2,)) [-1  1] Re_Reshape Reshape (Re_Reshape) allowzero=0 Re_Reshapecst->Re_Reshape Re_Reshape1 Reshape (Re_Reshape1) allowzero=0 Re_Reshapecst->Re_Reshape1 variable1 variable1 variable1->Re_Reshape LinearRegressor->variable1 variable2 variable2 variable2->Re_Reshape1 LinearRegressor1->variable2 Re_reshaped0 Re_reshaped0 Co_Concat Concat (Co_Concat) axis=1 Re_reshaped0->Co_Concat Re_Reshape->Re_reshaped0 Re_reshaped02 Re_reshaped02 Re_reshaped02->Co_Concat Re_Reshape1->Re_reshaped02 Co_Concat->variable