GaussianProcessRegressor - ~b-reg-NF-cov-64 - dotproduct -#

Fitted on a problem type ~b-reg-NF-cov-64 (see find_suitable_problem), method predict matches output .

GaussianProcessRegressor(alpha=100.0, kernel=DotProduct(sigma_0=1),
                     random_state=42)

index

0

skl_nop

1

onx_size

606

onx_nnodes

7

onx_ninits

2

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_Identity

1

onx_size_optim

565

onx_nnodes_optim

6

onx_ninits_optim

2
%0 X X double((0, 4)) Sh_Shape Shape (Sh_Shape) X->Sh_Shape Tr_Transpose Transpose (Tr_Transpose) perm=[1 0] X->Tr_Transpose Ma_MatMul MatMul (Ma_MatMul) X->Ma_MatMul GPmean GPmean double((0, 1)) GPcovstd GPcovstd double(('?',)) Re_ReduceSumcst Re_ReduceSumcst int64((1,)) [1] Re_ReduceSum ReduceSum (Re_ReduceSum) keepdims=1 Re_ReduceSumcst->Re_ReduceSum Ad_Addcst Ad_Addcst float64((1,)) [1.] Ad_Add Add (Ad_Add) Ad_Addcst->Ad_Add Sh_shape0 Sh_shape0 Co_ConstantOfShape ConstantOfShape (Co_ConstantOfShape) value=[0.] Sh_shape0->Co_ConstantOfShape Sh_Shape->Sh_shape0 Tr_transposed0 Tr_transposed0 Tr_transposed0->Ma_MatMul Tr_Transpose->Tr_transposed0 Ma_Y0 Ma_Y0 Ma_Y0->Ad_Add Ma_MatMul->Ma_Y0 Co_output0 Co_output0 Co_output0->Re_ReduceSum Co_ConstantOfShape->Co_output0 Ad_C0 Ad_C0 Id_Identity Identity (Id_Identity) Ad_C0->Id_Identity Ad_Add->Ad_C0 Re_ReduceSum->GPmean Id_Identity->GPcovstd

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