OneVsOneClassifier - ~m-cl-nop - logreg - {‘zipmap’: False}#
Fitted on a problem type ~m-cl-nop
(see find_suitable_problem
),
method predict matches output .
Model was converted with additional parameter: <class 'sklearn.multiclass.OneVsOneClassifier'>={'zipmap': False}
.
OneVsOneClassifier(estimator=LogisticRegression(random_state=0,
solver='liblinear'),
n_jobs=8)
index |
0 |
---|---|
skl_nop |
4 |
skl_ncoef |
3 |
skl_nlin |
3 |
onx_size |
3551 |
onx_nnodes |
53 |
onx_ninits |
10 |
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 |
17 |
|
onx_ai.onnx.ml |
1 |
onx_op_Cast |
3 |
onx_op_Identity |
1 |
onx_op_Reshape |
6 |
onx_size_optim |
3399 |
onx_nnodes_optim |
49 |
onx_ninits_optim |
10 |
fit_classes_.shape |
3 |
3 |
|
fit_estimators_.size |
3 |
fit_estimators_.coef_.shape |
(1, 4) |
fit_estimators_.classes_.shape |
2 |
fit_estimators_.intercept_.shape |
1 |
fit_estimators_.n_iter_.shape |
1 |