Python API

Data Structure API

Dataset(data[, label, reference, weight, …])	Dataset in LightGBM.
Booster([params, train_set, model_file, …])	Booster in LightGBM.
CVBooster()	CVBooster in LightGBM.

Training API

train(params, train_set[, num_boost_round, …])	Perform the training with given parameters.
cv(params, train_set[, num_boost_round, …])	Perform the cross-validation with given paramaters.

Scikit-learn API

LGBMModel([boosting_type, num_leaves, …])	Implementation of the scikit-learn API for LightGBM.
LGBMClassifier([boosting_type, num_leaves, …])	LightGBM classifier.
LGBMRegressor([boosting_type, num_leaves, …])	LightGBM regressor.
LGBMRanker([boosting_type, num_leaves, …])	LightGBM ranker.

Dask API

New in version 3.2.0.

DaskLGBMClassifier([boosting_type, …])	Distributed version of lightgbm.LGBMClassifier.
DaskLGBMRegressor([boosting_type, …])	Distributed version of lightgbm.LGBMRegressor.
DaskLGBMRanker([boosting_type, num_leaves, …])	Distributed version of lightgbm.LGBMRanker.

Callbacks

early_stopping(stopping_rounds[, …])	Create a callback that activates early stopping.
print_evaluation([period, show_stdv])	Create a callback that prints the evaluation results.
record_evaluation(eval_result)	Create a callback that records the evaluation history into eval_result.
reset_parameter(**kwargs)	Create a callback that resets the parameter after the first iteration.

Plotting

plot_importance(booster[, ax, height, xlim, …])	Plot model’s feature importances.
plot_split_value_histogram(booster, feature)	Plot split value histogram for the specified feature of the model.
plot_metric(booster[, metric, …])	Plot one metric during training.
plot_tree(booster[, ax, tree_index, …])	Plot specified tree.
create_tree_digraph(booster[, tree_index, …])	Create a digraph representation of specified tree.

Utilities

register_logger(logger)

Register custom logger.