20f388cfe01635a2073723c5c4ffd6dd7a87fbb2,tensorflow_hub/tools/module_search/utils.py,,knn_errorrate_loo,#,140

Before Change

  cnt = 0
  for i in range(np.shape(d)[0]):
    cnt_i = 0
    for j in range(k):
      if y[i] != y[indices[i, j]]:
        cnt_i += 1
    if cnt_i >= k / 2.0:
      cnt += 1

  return float(cnt) / np.shape(d)[0]

After Change

  for i in range(np.shape(d)[0]):

    // Get max vote
    labels = y[indices[i, :k]]
    keys, counts = np.unique(labels, return_counts=True)
    maxkey = keys[np.argmax(counts)]
    if y[i] != maxkey:
      cnt += 1

Instances