LogisticRegression - ~m-cl-dec - liblinear-dec - {‘raw_scores’: True, ‘zipmap’: False}#

Fitted on a problem type ~m-cl-dec (see find_suitable_problem), method decision_function matches output . Model was converted with additional parameter: <class 'sklearn.linear_model._logistic.LogisticRegression'>={'raw_scores': True, 'zipmap': False}.

LogisticRegression(n_jobs=8, random_state=0, solver='liblinear')

index

0

skl_nop

1

skl_ncoef

3

skl_nlin

1

onx_size

426

onx_nnodes

1

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_

15

onx_size_optim

426

onx_nnodes_optim

1

onx_ninits_optim

0

fit_classes_.shape

3

fit_coef_.shape

(3, 4)

fit_intercept_.shape

3

fit_n_iter_.shape

1