TweedieRegressor - b-reg - default -#

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

TweedieRegressor()

index

0

skl_nop

1

skl_ncoef

4

skl_nlin

1

onx_size

362

onx_nnodes

3

onx_ninits

3

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_op_Reshape

1

onx_size_optim

362

onx_nnodes_optim

3

onx_ninits_optim

3

fit_intercept_.shape

1

fit_coef_.shape

4

%0 X X float((0, 4)) Ma_MatMul MatMul (Ma_MatMul) X->Ma_MatMul variable variable float((0, 1)) Ma_MatMulcst Ma_MatMulcst float32((4,)) [ 0.08625456 -0.04117553  0.39916316  0.19531801] Ma_MatMulcst->Ma_MatMul Ad_Addcst Ad_Addcst float32((1,)) [-0.3263043] Ad_Add Add (Ad_Add) Ad_Addcst->Ad_Add Re_Reshapecst Re_Reshapecst int64((2,)) [-1  1] Re_Reshape Reshape (Re_Reshape) Re_Reshapecst->Re_Reshape Ma_Y0 Ma_Y0 Ma_Y0->Ad_Add Ma_MatMul->Ma_Y0 Ad_C0 Ad_C0 Ad_C0->Re_Reshape Ad_Add->Ad_C0 Re_Reshape->variable