TruncatedSVD - num-tr - default -#

Fitted on a problem type num-tr (see find_suitable_problem), method transform matches output .

TruncatedSVD(random_state=0)

index

0

skl_nop

1

onx_size

241

onx_nnodes

1

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_

13

onx_size_optim

241

onx_nnodes_optim

1

onx_ninits_optim

1

fit_components_.shape

(2, 4)

fit_explained_variance_.shape

2

fit_explained_variance_ratio_.shape

2

fit_singular_values_.shape

2

%0 X X float((0, 4)) SklearnTruncatedSVD MatMul (SklearnTruncatedSVD) X->SklearnTruncatedSVD variable variable float((0, 2)) transform_matrix transform_matrix float32((4, 2)) [[ 0.75457555  0.29342988] [ 0.37440276  0.5413836 ] [ 0.51346946 -0.7380332 ] [ 0.16366868 -0.27588028]] transform_matrix->SklearnTruncatedSVD SklearnTruncatedSVD->variable