def METHOD_NAME(self, X, known_cat_bitsets, f_idx_map, n_threads):
    """Predict raw values for non-binned data.
    Parameters
    ----------
    X : ndarray, shape (n_samples, n_features)
        The input samples.
    known_cat_bitsets : ndarray of shape (n_categorical_features, 8)
        Array of bitsets of known categories, for each categorical feature.
    f_idx_map : ndarray of shape (n_features,)
        Map from original feature index to the corresponding index in the
        known_cat_bitsets array.
    n_threads : int
        Number of OpenMP threads to use.
    Returns
    -------
    y : ndarray, shape (n_samples,)
        The raw predicted values.
    """
    out = np.empty(X.shape[0], dtype=Y_DTYPE)
    _predict_from_raw_data(
        self.nodes,
        X,
        self.raw_left_cat_bitsets,
        known_cat_bitsets,
        f_idx_map,
        n_threads,
        out,
    )
    return out