Scikit-Learn API

LGBMClassifier

Constructor

LGBMClassifier(*args, **kwargs)

LightGBM classifier.

Attributes

LGBMClassifier.fit(X, y[, sample_weight, ...])	Build a gradient boosting model from the training set (X, y).
LGBMClassifier.get_params([deep])	Get parameters for this estimator.
LGBMClassifier.load_model(model)
LGBMClassifier.predict(X, **kwargs)	Return the predicted value for each sample.
LGBMClassifier.predict_proba(X, **kwargs)	Return the predicted probability for each class for each sample.
LGBMClassifier.score(X, y[, sample_weight])	Return the mean accuracy on the given test data and labels.
LGBMClassifier.set_params(**params)	Set the parameters of this estimator.
LGBMClassifier.to_local()

LGBMRegressor

Constructor

LGBMRegressor(*args, **kwargs)

LightGBM regressor.

Attributes

LGBMRegressor.fit(X, y[, sample_weight, ...])	Build a gradient boosting model from the training set (X, y).
LGBMRegressor.get_params([deep])	Get parameters for this estimator.
LGBMRegressor.load_model(model)
LGBMRegressor.predict(X, **kw)	Return the predicted value for each sample.
LGBMRegressor.predict_proba(X, **kwargs)
LGBMRegressor.score(X, y[, sample_weight])	Return the coefficient of determination of the prediction.
LGBMRegressor.set_params(**params)	Set the parameters of this estimator.
LGBMRegressor.to_local()

LGBMRanker

Constructor

LGBMRanker(*args, **kwargs)

LightGBM ranker.

Attributes

LGBMRanker.fit(X, y[, sample_weight, ...])	Build a gradient boosting model from the training set (X, y).
LGBMRanker.get_params([deep])	Get parameters for this estimator.
LGBMRanker.load_model(model)
LGBMRanker.predict(X, **kw)	Return the predicted value for each sample.
LGBMRanker.predict_proba(X, **kwargs)
LGBMRanker.set_params(**params)	Set the parameters of this estimator.
LGBMRanker.to_local()