Function expand_grid_recursive

crates/openquant/src/hyperparameter_tuning.rs:206–225

(
    keys: &[String],
    idx: usize,
    grid: &BTreeMap<String, Vec<HyperParamValue>>,
    current: &mut ParamSet,
    out: &mut Vec<ParamSet>,
)

    }

    if sum_w <= 0.0 {
        return Err(TuningError::ZeroSampleWeightSum);
    }

    let accuracy = weighted_correct / sum_w;
    let neg_log_loss = -(weighted_loss / sum_w);

    match scoring {
        SearchScoring::Accuracy => Ok(accuracy),
        SearchScoring::NegLogLoss => Ok(neg_log_loss),
        SearchScoring::BalancedAccuracy => {
            // Handle single-class folds by averaging recall over classes present in the fold.
            let mut recalls = Vec::new();
            if pos_total > 0.0 {
                recalls.push(pos_correct / pos_total);
            }
            if neg_total > 0.0 {
                recalls.push(neg_correct / neg_total);
            }
            if recalls.is_empty() {
                return Err(TuningError::NoLabeledSamples);
            }
            Ok(recalls.iter().sum::<f64>() / recalls.len() as f64)