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.