train.py 文件源码

def munge_scoreses(scoreses, df):
  npredictors = len(scoreses)
  score_shape = (len(df), npredictors)
  scores = np.empty(score_shape, dtype=np.float32)
  # Yay, nested loops :/
  i = 0
  for (uid, pid) in df[ ['uid', 'pid'] ].itertuples(index=False):
    for predictor_ix, pdict in enumerate(scoreses):
      prob = pdict[uid][pid]
      scores[i, predictor_ix] = logit(prob)
    i += 1

  return scores