bhalml/play_golf_select_algorithm
0
1��6 �xgboost.sklearn��
XGBClassifier���)��}�(� n_estimators�Kd� objective��binary:logistic�� max_depth�K�2max_leaves�N�max_bin�N� grow_policy�N�
learning_rate�G?�333333� verbosity�N�booster�N� tree_method�N�gamma�N�min_child_weight�N�max_delta_step�N� subsample�N�sampling_method�N�colsample_bytree�N�colsample_bylevel�N�colsample_bynode�N� reg_alpha�N�3reg_lambda�N�scale_pos_weight�N�4base_score�N�missing�G� �num_parallel_tree�K� random_state�N�n_jobs�N�monotone_constraints�N�interaction_constraints�N�importance_type�N�device�N�validate_parameters�N�enable_categorical���
feature_types�N�max_cat_to_onehot�N�max_cat_threshold�N�multi_strategy�N� eval_metric�N�early_stopping_rounds�N� callbacks�N�5n_classes_�K�_Booster�� xgboost.core��Booster���)��}��handle��builtins�� bytearray���B M {L Config{L learner{L
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learning_rateSL 0.300000012L max_binSL 256L max_cat_thresholdSL 64L max_cat_to_onehotSL 4L max_delta_stepSL 0L max_depthSL 3L 6max_leavesSL 0L min_child_weightSL 1L min_split_lossSL 0L monotone_constraintsSL ()L refresh_leafSL 1L reg_alphaSL 0L 7reg_lambdaSL 1L sampling_methodSL uniformL sketch_ratioSL 2L sparse_thresholdSL 0.20000000000000001L subsampleSL 1}L updater[#L {L hist_train_param{L debug_synchronizeSL 0L max_cached_hist_nodeSL 65536}L nameSL grow_quantile_histmaker}}L learner_model_param{L 8base_scoreSL 5.825702E-1L boost_from_averageSL 1L num_classSL 0L num_featureSL 6L 9num_targetSL 1}L learner_train_param{L boosterSL gbtreeL disable_default_eval_metricSL 0L multi_strategySL one_output_per_treeL objectiveSL binary:logistic}L metrics[#L {L nameSL logloss}L objective{L nameSL binary:logisticL reg_loss_param{L scale_pos_weightSL 1}}}L version[#L ii i}L Model{L learner{L 10attributes{}L
feature_names[#L SL WindySL
Outlook_RainySL
Outlook_SunnySL Temp_HotSL Temp_MildSL Humidity_NormalL
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