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();

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];