MLPRegressor - b-reg - default -#

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

MLPRegressor(random_state=0)

index

0

skl_nop

1

onx_size

3026

onx_nnodes

7

onx_ninits

5

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_

14

onx_op_Cast

1

onx_op_Reshape

1

onx_size_optim

3026

onx_nnodes_optim

7

onx_ninits_optim

5

fit_best_loss_.shape

1

fit_loss_.shape

1
%0 X X float((0, 4)) Cast Cast (Cast) to=1 X->Cast variable variable float((0, 1)) coefficient coefficient float32((4, 100)) [[ 2.22727489e-02  9.08409730e-02  6.74837753e-02 ... MatMul MatMul (MatMul) coefficient->MatMul intercepts intercepts float32((1, 100)) [[-0.04214729  0.19814537 -0.17549938  0.17815948 ... Add Add (Add) intercepts->Add coefficient1 coefficient1 float32((100, 1)) [[-1.12573214e-01] [-3.59173343e-02] [-3.3781398... MatMul1 MatMul (MatMul1) coefficient1->MatMul1 intercepts1 intercepts1 float32((1, 1)) [[-0.15396143]] Add1 Add (Add1) intercepts1->Add1 shape_tensor shape_tensor int64((2,)) [-1  1] Reshape Reshape (Reshape) shape_tensor->Reshape cast_input cast_input cast_input->MatMul Cast->cast_input mul_result mul_result mul_result->Add MatMul->mul_result add_result add_result Relu Relu (Relu) add_result->Relu Add->add_result next_activations next_activations next_activations->MatMul1 Relu->next_activations mul_result1 mul_result1 mul_result1->Add1 MatMul1->mul_result1 add_result1 add_result1 add_result1->Reshape Add1->add_result1 Reshape->variable

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MLPClassifier - ~m-label - default - {‘zipmap’: False}

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MLPRegressor - m-reg - default -