PLSRegression - ~b-reg-64 - default -#

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

PLSRegression()

index

0

skl_nop

1

skl_ncoef

4

skl_nlin

1

onx_size

479

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

479

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 double((0, 4)) Su_Sub Sub (Su_Sub) X->Su_Sub variable variable double((0, 1)) Su_Subcst Su_Subcst float64((4,)) [5.86033924 2.99788182 3.75989191 1.18838401] Su_Subcst->Su_Sub Di_Divcst Di_Divcst float64((4,)) [0.83825724 0.52938169 1.78026067 0.71215553] Di_Div Div (Di_Div) Di_Divcst->Di_Div Ma_MatMulcst Ma_MatMulcst float64((4, 1)) [[-0.06400424] [-0.0238454 ] [ 0.60557162] [ 0.62353582]] Ma_MatMul MatMul (Ma_MatMul) Ma_MatMulcst->Ma_MatMul Ad_Addcst Ad_Addcst float64((1,)) [1.78866071] 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