OneClassSVM - outlier - default -#

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

OneClassSVM()

index

0

skl_nop

1

onx_size

1944

onx_nnodes

4

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

2

onx_size_optim

1944

onx_nnodes_optim

4

onx_ninits_optim

0

fit_class_weight_.shape

0

fit_support_.shape

58

fit_support_vectors_.shape

(58, 4)

fit_dual_coef_.shape

(1, 58)

fit_intercept_.shape

1

fit_offset_.shape

1

%0 X X float((0, 4)) SVM SVMRegressor (SVM) coefficients=[1.         1.    ... kernel_params=[0.06311981 0.   ... kernel_type=b'RBF' n_supports=58 post_transform=b'NONE' rho=[-32.510128] support_vectors=[ 4.3017502e+00... X->SVM label label int64((0, 1)) scores scores float((0, 1)) N2 Sign (N2) scores->N2 SVMO1 SVMO1 Cast Cast (Cast) to=1 SVMO1->Cast SVM->SVMO1 Cast->scores float_prediction float_prediction Cast1 Cast (Cast1) to=7 float_prediction->Cast1 N2->float_prediction Cast1->label