SVC - b-cl - rbf - {‘zipmap’: False}#

Fitted on a problem type b-cl (see find_suitable_problem), method predict_proba matches output . Model was converted with additional parameter: <class 'sklearn.svm._classes.SVC'>={'zipmap': False}.

SVC(probability=True, random_state=0)

index

0

skl_nop

1

onx_size

833

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

833

onx_nnodes_optim

2

onx_ninits_optim

0

fit_class_weight_.shape

2

fit_classes_.shape

2

fit_support_.shape

14

fit_support_vectors_.shape

(14, 4)

fit_dual_coef_.shape

(1, 14)

fit_intercept_.shape

1
%0 X X float((0, 4)) SVMc SVMClassifier (SVMc) classlabels_ints=[0 1] coefficients=[ 0.6410916   0.91... kernel_params=[0.06311981 0.   ... kernel_type=b'RBF' post_transform=b'NONE' prob_a=[-3.1239798] prob_b=[0.2592278] rho=[-0.09855022] support_vectors=[5.402252   3.5... vectors_per_class=[7 7] X->SVMc label label int64((0,)) probabilities probabilities float((0, 2)) SVM02 SVM02 Cast Cast (Cast) to=1 SVM02->Cast SVMc->label SVMc->SVM02 Cast->probabilities

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SVC - b-cl - sigmoid - {‘zipmap’: False}