sklearn.feature_selection中chi2的“ ValueError：长度必须匹配才能进行比较”

Question

I am trying to run the following but running into an error: ValueError: Lengths must match to compare

from sklearn.feature_selection import chi2
import numpy as np

N = 2
for Product, category_id in sorted(category_to_id.items()):
  features_chi2 = chi2(features, labels == category_id)
  indices = np.argsort(features_chi2[0])
  feature_names = np.array(tfidf.get_feature_names())[indices]
  unigrams = [v for v in feature_names if len(v.split(' ')) == 1]
  bigrams = [v for v in feature_names if len(v.split(' ')) == 2]
  print("# '{}':".format(Product))
  print("  . Most correlated unigrams:\n       . {}".format('\n       . '.join(unigrams[-N:])))
  print("  . Most correlated bigrams:\n       . {}".format('\n       . '.join(bigrams[-N:])))

The code is from https://towardsdatascience.com/multi-class-text-classification-with-scikit-learn-12f1e60e0a9f

Output is:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-45-bbfd1a1f6a1a> in <module>()
      3 N = 2
      4 for Product, category_id in sorted(category_to_id.items()):
----> 5     features_chi2 = chi2(features, labels == category)
      6     indices = np.argsort(features_chi2[0])
      7     feature_names = np.array(tfidf.get_feature_names())[indices]

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\ops.py in wrapper(self, other, axis)
   1221             # as it will broadcast
   1222             if other.ndim != 0 and len(self) != len(other):
-> 1223                 raise ValueError('Lengths must match to compare')
   1224 
   1225             res_values = na_op(self.values, np.asarray(other))

ValueError: Lengths must match to compare

len(features) and len(labels) prints the same counts.

Answer 1

Your traceback has labels == category in line 5. But in the code you have labels == category_id . So this is probably the source of your error.