GradientBoostingClassifier - m-cl - default - {‘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._gb.GradientBoostingClassifier'>={'zipmap': False}.
GradientBoostingClassifier(n_estimators=200, random_state=0)
index |
0 |
|---|---|
skl_nop |
201 |
skl_nnodes |
2876 |
skl_ntrees |
200 |
skl_max_depth |
3 |
onx_size |
310105 |
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 |
15 |
|
onx_size_optim |
310105 |
onx_nnodes_optim |
1 |
onx_ninits_optim |
0 |
fit_classes_.shape |
3 |
fit_estimators_.shape |
3 |
fit_train_score_.shape |
200 |
3 |
|
4 |
|
fit_estimators_.size |
200 |
fit_estimators_.sum|.sum|tree_.leave_count |
4382 |
fit_estimators_.sum|.sum|tree_.node_count |
8164 |
fit_estimators_..n_features_ |
4 |
fit_estimators_.max|.max|tree_.max_depth |
3 |