def select(self, x, y, n_keep):
        cnts = y.value_counts()
        logging.info("Computing binary feature scores for %d features..." % len(x.columns))
        if len(cnts) > 2:
            scores = self.round_robin(x, y, n_keep)
        else:
            scores = self.rank(x, y)
            scores = [s[1] for s in scores]
        logging.debug(scores[:200])
        return scores[:n_keep]
dataset/ETHPy150Open kvh/ramp/ramp/selectors.py/BinaryFeatureSelector.select/original