VotingClassifier - m-cl - logreg-noflatten - {‘zipmap’: False}

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

VotingClassifier(estimators=[('lr1', LogisticRegression(solver='liblinear')),
                         ('lr2',
                          LogisticRegression(fit_intercept=False,
                                             solver='liblinear'))],
             flatten_transform=False, n_jobs=8, voting='soft')

index	0
skl_nop	3
skl_ncoef	6
skl_nlin	2
onx_size	1498
onx_nnodes	12
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	1.13.1
onx_	17
onx_ai.onnx.ml	1
onx_op_Cast	2
onx_op_Reshape	1
onx_size_optim	1472
onx_nnodes_optim	12
onx_ninits_optim	3
fit_classes_.shape	3
fit_estimators_.size	2
fit_estimators_.intercept_.shape	3
fit_estimators_.n_iter_.shape	3
fit_estimators_.coef_.shape	(3, 4)
fit_estimators_.classes_.shape	3