Python API

Data Structure API

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

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.