PLSRegression - b-reg - default -#

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

PLSRegression()

index

0

skl_nop

1

skl_ncoef

4

skl_nlin

1

onx_size

427

onx_nnodes

4

onx_ninits

4

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_size_optim

427

onx_nnodes_optim

4

onx_ninits_optim

4

fit_x_weights_.shape

(4, 2)

fit_y_weights_.shape

(1, 2)

fit_x_loadings_.shape

(4, 2)

fit_y_loadings_.shape

(1, 2)

fit_x_rotations_.shape

(4, 2)

fit_y_rotations_.shape

(1, 2)

fit_coef_.shape

(4, 1)

%0 X X float((0, 4)) Su_Sub Sub (Su_Sub) X->Su_Sub variable variable float((0, 1)) Su_Subcst Su_Subcst float32((4,)) [5.860339 2.997882 3.759892 1.188384] Su_Subcst->Su_Sub Di_Divcst Di_Divcst float32((4,)) [0.83825725 0.5293817  1.7802607  0.7121555 ] Di_Div Div (Di_Div) Di_Divcst->Di_Div Ma_MatMulcst Ma_MatMulcst float32((4, 1)) [[-0.06400429] [-0.0238454 ] [ 0.6055717 ] [ 0.6235358 ]] Ma_MatMul MatMul (Ma_MatMul) Ma_MatMulcst->Ma_MatMul Ad_Addcst Ad_Addcst float32((1,)) [1.7886608] Ad_Add Add (Ad_Add) Ad_Addcst->Ad_Add Su_C0 Su_C0 Su_C0->Di_Div Su_Sub->Su_C0 Di_C0 Di_C0 Di_C0->Ma_MatMul Di_Div->Di_C0 Ma_Y0 Ma_Y0 Ma_Y0->Ad_Add Ma_MatMul->Ma_Y0 Ad_Add->variable