|
| | fit (self, X, y, sample_weight=None, init_score=None, group=None, eval_set=None, eval_names=None, eval_sample_weight=None, eval_init_score=None, eval_group=None, eval_metric=None, eval_at=[1], early_stopping_rounds=None, verbose=True, feature_name='auto', categorical_feature='auto', callbacks=None) |
| |
| | __init__ (self, boosting_type='gbdt', num_leaves=31, max_depth=-1, learning_rate=0.1, n_estimators=100, subsample_for_bin=200000, objective=None, class_weight=None, min_split_gain=0., min_child_weight=1e-3, min_child_samples=20, subsample=1., subsample_freq=0, colsample_bytree=1., reg_alpha=0., reg_lambda=0., random_state=None, n_jobs=-1, silent=True, importance_type='split', **kwargs) |
| |
| | get_params (self, deep=True) |
| |
| | set_params (self, **params) |
| |
| | predict (self, X, raw_score=False, num_iteration=None, pred_leaf=False, pred_contrib=False, **kwargs) |
| |
| | n_features_ (self) |
| |
| | best_score_ (self) |
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| | best_iteration_ (self) |
| |
| | objective_ (self) |
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| | booster_ (self) |
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| | evals_result_ (self) |
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| | feature_importances_ (self) |
| |
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| _eval_at |
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| _Booster |
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| _evals_result |
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| _best_score |
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| _best_iteration |
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| _other_params |
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| _objective |
| |
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| _n_features |
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| _classes |
| |
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| _n_classes |
| |
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| _fobj |
| |
|
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| _base_doc = LGBMModel.fit.__doc__ |
| |
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| _before_early_stop |
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| _early_stop |
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| _after_early_stop |
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| boosting_type |
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| objective |
| |
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| num_leaves |
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| max_depth |
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| learning_rate |
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| n_estimators |
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| subsample_for_bin |
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| min_split_gain |
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| min_child_weight |
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| min_child_samples |
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| subsample |
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| subsample_freq |
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| colsample_bytree |
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| reg_alpha |
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| reg_lambda |
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| random_state |
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| n_jobs |
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| silent |
| |
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| importance_type |
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| class_weight |
| |
◆ fit()
| lightgbm.sklearn.LGBMRanker.fit |
( |
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self, |
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|
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X, |
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y, |
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sample_weight = None, |
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init_score = None, |
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|
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group = None, |
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|
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eval_set = None, |
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eval_names = None, |
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eval_sample_weight = None, |
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|
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eval_init_score = None, |
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eval_group = None, |
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|
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eval_metric = None, |
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eval_at = [1], |
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|
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early_stopping_rounds = None, |
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|
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verbose = True, |
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feature_name = 'auto', |
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categorical_feature = 'auto', |
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|
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callbacks = None |
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) |
| |
The documentation for this class was generated from the following file:
- External/LightGBM_2.2.3/LightGBM-2.2.3/python-package/lightgbm/sklearn.py
Public Member Functions inherited from lightgbm.sklearn.LGBMModel