How to use the suod.utils.utility.raw_score_to_proba function in suod

X = check_array(X)

    pred = []
    for i in range(n_estimators):
        estimator = clfs[i]
        if verbose > 1:
            print("predicting with estimator %d of %d for this parallel run "
                  "(total %d)..." % (i + 1, n_estimators, total_n_estimators))

        # project matrix
        X_scaled = jl_transform(X, rp_transformers[i])

        # turn approximator scores to labels by outlier
        if approx_flags[i] == 1:
            raw_scores = approximators[i].predict(X_scaled)
            predicted_scores = raw_score_to_proba(estimator.decision_scores_,
                                                  raw_scores)

        else:
            predicted_scores = estimator.predict_proba(X_scaled)

        pred.append(predicted_scores[:, 1])
        # pred.append(predicted_scores)

    return pred