SVR - b-reg - linear -#

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

SVR(kernel='linear')

index

0

skl_nop

1

skl_ncoef

1

skl_nlin

1

onx_size

2752

onx_nnodes

2

onx_ninits

0

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_ai.onnx.ml

1

onx_

9

onx_op_Cast

1

onx_size_optim

2752

onx_nnodes_optim

2

onx_ninits_optim

0

fit_class_weight_.shape

0

fit_support_.shape

95

fit_support_vectors_.shape

(95, 4)

fit_dual_coef_.shape

(1, 95)

fit_intercept_.shape

1

%0 X X float((0, 4)) SVM SVMRegressor (SVM) coefficients=[ 1.         -1.  ... kernel_params=[0.06311981 0.   ... kernel_type=b'LINEAR' n_supports=95 post_transform=b'NONE' rho=[0.15157957] support_vectors=[ 5.9683514e+00... X->SVM variable variable float((0, 1)) SVM03 SVM03 Cast Cast (Cast) to=1 SVM03->Cast SVM->SVM03 Cast->variable