The how well do the features plus a constant base rate sum up to the model output.

def local_accuracy(X_train, y_train, X_test, y_test, attr_test, model_generator, metric, trained_model):
    """ The how well do the features plus a constant base rate sum up to the model output.
    """

    X_train, X_test = to_array(X_train, X_test)

    # how many features to mask
    assert X_train.shape[1] == X_test.shape[1]

    # keep nkeep top features and re-train the model for each test explanation
    yp_test = trained_model.predict(X_test)

    return metric(yp_test, strip_list(attr_test).sum(1))