Function _std

python/openquant/feature_diagnostics.py:238–243

(values: Sequence[float])

    if scoring == "f1":
        tp = sum(w for y, p, w in zip(y_true, pred, weights) if y > 0.5 and p > 0.5)
        fp = sum(w for y, p, w in zip(y_true, pred, weights) if y <= 0.5 and p > 0.5)
        fn = sum(w for y, p, w in zip(y_true, pred, weights) if y > 0.5 and p <= 0.5)
        precision = tp / (tp + fp) if tp + fp > 0 else 0.0
        recall = tp / (tp + fn) if tp + fn > 0 else 0.0
        return 2.0 * precision * recall / (precision + recall) if precision + recall > 0 else 0.0

    raise ValueError("scoring must be one of: neg_log_loss, accuracy, f1")