Installation

cargo add lightgbm3

for Linux:

apt install -y cmake clang libclang-dev libc++-dev gcc-multilib

for Mac:

brew install cmakebrew install libomp # only required if you compile with "openmp" feature

for Windows

Usage

Training:

use lightgbm3::{Dataset,Booster};use serde_json::json;let features =vec![vec![1.0,0.1,0.2],                    vec![0.7,0.4,0.5],                    vec![0.9,0.8,0.5],                    vec![0.2,0.2,0.8],                    vec![0.1,0.7,1.0]];let labels =vec![0.0,0.0,0.0,1.0,1.0];let dataset =Dataset::from_vec_of_vec(features, labels,true).unwrap();let params =json!{{"num_iterations":10,"objective":"binary","metric":"auc",}};let bst =Booster::train(dataset,&params).unwrap();bst.save_file("path/to/model.lgb").unwrap();

Inference:

use lightgbm3::{Dataset,Booster};let bst =Booster::from_file("path/to/model.lgb").unwrap();let features =vec![1.0,2.0, -5.0];let n_features = features.len();let y_pred = bst.predict_with_params(&features, n_featuresasi32,true,"num_threads=1").unwrap()[0];

Features

Benchmarks

cargo bench

Development

git clone --recursive https://github.com/Mottl/lightgbm3-rs.git

Thanks