Function test_sb_classifier

crates/openquant/tests/sb_bagging.rs:165–192

()

#[test]
fn test_sb_classifier() {
    let (x, y, _, _ind) = synthetic_dataset();
    let split = (x.nrows() as f64 * 0.6) as usize;
    let x_train = x.rows(0, split).into_owned();
    let x_test = x.rows(split, x.nrows() - split).into_owned();
    let y_train = &y[0..split];
    let y_test = &y[split..];

    let mut sb = SequentiallyBootstrappedBaggingClassifier::new(1);
    sb.n_estimators = 100;
    sb.max_features = MaxFeatures::Float(1.0);
    sb.oob_score = true;

    // indicator matrix needs the same number of labels as rows in train set
    let bar_index: Vec<usize> = (0..split).collect();
    let t1: Vec<(usize, usize)> =
        (0..split.saturating_sub(4)).step_by(2).map(|s| (s, s + 4)).collect();
    let ind_train = get_ind_matrix(&t1, &bar_index);

    sb.fit(&x_train, y_train, &ind_train, None).unwrap();
    let preds = sb.predict(&x_test).unwrap();

    let acc = preds.iter().zip(y_test.iter()).filter(|(p, t)| **p == **t).count() as f64
        / y_test.len() as f64;

    assert!(acc >= 0.55, "acc={acc}");
    assert!(sb.oob_score_value.unwrap_or(0.0).is_finite());
}

#[test]
fn test_sb_regressor() {