XGBClassifier - m-cl - default -#

Fitted on a problem type m-cl (see find_suitable_problem), method predict_proba matches output .

XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,
          colsample_bynode=1, colsample_bytree=1, enable_categorical=False,
          gamma=0, gpu_id=-1, importance_type=None,
          interaction_constraints='', learning_rate=0.300000012,
          max_delta_step=0, max_depth=6, min_child_weight=1, missing=nan,
          monotone_constraints='()', n_estimators=100, n_jobs=8,
          num_parallel_tree=1, objective='multi:softprob', predictor='auto',
          random_state=0, reg_alpha=0, reg_lambda=1, scale_pos_weight=None,
          subsample=1, tree_method='exact', validate_parameters=1,
          verbosity=None)

index

0

skl_nop

1

onx_size

43873

onx_nnodes

3

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_op_ZipMap

1

onx_size_optim

43873

onx_nnodes_optim

3

onx_ninits_optim

0

fit_classes_.shape

3

fit_n_classes_

3

fit_objective

multi:softprob

fit_estimators_.size

300

fit_node_count

1336

fit_ntrees

300

fit_leave_count

818

fit_mode_count

2