Crate lightgbm3

LightGBM Rust library

lightgbm3 supports the following features:

• polars for polars support
• openmp for multi-processing support
• gpu for GPU support
• cuda for CUDA support

Examples

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_features as i32, true, "num_threads=1").unwrap()[0];

Structs

Booster

Core model in LightGBM, containing functions for training, evaluating and predicting.

Dataset

LightGBM Dataset

Error

Wrap errors returned by the LightGBM library.

Enums

ImportanceType

Type of feature importance

Traits

DType

LightGBM dtype

Functions

argmax

Get index of the element in a slice with the maximum value

Type Aliases

Result

Convenience return type for most operations which can return an LightGBM.