Java library and command-line application for converting LightGBM models to PMML.

• LightGBM 2.0.0 or newer.
• Java 1.8 or newer.

Enter the project root directory and build using Apache Maven:

mvn clean install

The build produces an executable uber-JAR file target/jpmml-lightgbm-executable-1.3-SNAPSHOT.jar.

A typical workflow can be summarized as follows:

1. Use LightGBM to train a model.
2. Save the model to a text file in a local filesystem.
3. Use the JPMML-LightGBM command-line converter application to turn this text file to a PMML file.

Using the lightgbm package to train a regression model for the example Boston housing dataset:

from sklearn.datasets import load_boston

boston = load_boston()

from lightgbm import LGBMRegressor

lgbm = LGBMRegressor(objective = "regression")
lgbm.fit(boston.data, boston.target, feature_name = boston.feature_names)

lgbm.booster_.save_model("lightgbm.txt")

Converting the text file lightgbm.txt to a PMML file lightgbm.pmml:

java -jar target/jpmml-lightgbm-executable-1.3-SNAPSHOT.jar --lgbm-input lightgbm.txt --pmml-output lightgbm.pmml

Getting help:

java -jar target/jpmml-lightgbm-executable-1.3-SNAPSHOT.jar --help

• Stacking Scikit-Learn, LightGBM and XGBoost models
• Deploying LightGBM models on Java/JVM platform
• Extending Scikit-Learn with GBDT plus LR ensemble (GBDT+LR) model type (Using LightGBM models on the GBDT side of GBDT+LR ensemble)
• Converting Scikit-Learn plus LightGBM pipelines to PMML documents

JPMML-LightGBM is licensed under the terms and conditions of the GNU Affero General Public License, Version 3.0.

If you would like to use JPMML-LightGBM in a proprietary software project, then it is possible to enter into a licensing agreement which makes JPMML-LightGBM available under the terms and conditions of the BSD 3-Clause License instead.

JPMML-LightGBM is developed and maintained by Openscoring Ltd, Estonia.

Interested in using Java PMML API software in your company? Please contact [email protected]