GridSearchCV - cluster - reg -#

Fitted on a problem type cluster (see find_suitable_problem), method predict matches output .

GridSearchCV(estimator=KMeans(random_state=0), n_jobs=1,
         param_grid={'n_clusters': [2, 3]})

index

0

skl_nop

1

onx_size

746

onx_nnodes

9

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_

14

onx_op_Identity

2

onx_size_optim

663

onx_nnodes_optim

7

onx_ninits_optim

3

fit_best_score_.shape

1
%0 X X float((0, 4)) Re_ReduceSumSquare ReduceSumSquare (Re_ReduceSumSquare) axes=[1] keepdims=1 X->Re_ReduceSumSquare Ge_Gemm Gemm (Ge_Gemm) alpha=-2.0 transB=1 X->Ge_Gemm label label int64((0,)) scores scores float((0, 3)) Ad_Addcst Ad_Addcst float32((3,)) [84.52504  39.141666 56.832886] Ad_Add1 Add (Ad_Add1) Ad_Addcst->Ad_Add1 Ge_Gemmcst Ge_Gemmcst float32((3, 4)) [[6.6014256  2.9432645  5.3828583  1.8188599 ] [5... Ge_Gemmcst->Ge_Gemm Mu_Mulcst Mu_Mulcst float32((1,)) [0.] Mu_Mul Mul (Mu_Mul) Mu_Mulcst->Mu_Mul Re_reduced0 Re_reduced0 Re_reduced0->Mu_Mul Ad_Add Add (Ad_Add) Re_reduced0->Ad_Add Re_ReduceSumSquare->Re_reduced0 Mu_C0 Mu_C0 Mu_C0->Ge_Gemm Mu_Mul->Mu_C0 Ge_Y0 Ge_Y0 Ge_Y0->Ad_Add Ge_Gemm->Ge_Y0 Ad_C01 Ad_C01 Ad_C01->Ad_Add1 Ad_Add->Ad_C01 Ad_C0 Ad_C0 Sq_Sqrt Sqrt (Sq_Sqrt) Ad_C0->Sq_Sqrt Ar_ArgMin ArgMin (Ar_ArgMin) axis=1 keepdims=0 Ad_C0->Ar_ArgMin Ad_Add1->Ad_C0 scores1 scores1 Identity1 Identity (Identity1) scores1->Identity1 Sq_Sqrt->scores1 label1 label1 Identity Identity (Identity) label1->Identity Ar_ArgMin->label1 Identity1->scores Identity->label

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