title: What do these F scores mean ? Using SelectKBest feature
body: <p>I am new to Statistics.I am trying to select the best features to do classification on my data set and I chose to do so by running SelectKbest from scikitlearn. </p>
  
  <p>Here is my code :</p>
  
  <pre><code> import sklearn.feature_selection as fs
   kb = fs.SelectKBest(k=10)
   kb.fit(X, y)
   names = X.columns.values[kb.get_support()]
   scores = kb.scores_[kb.get_support()]
   names_scores = list(zip(names, scores))
   ns_df = pd.DataFrame(data = names_scores, columns=
    ['Feat_names','F_Scores'])
   ns_df_sorted = ns_df.sort_values(['F_Scores','Feat_names'], ascending =
    [False, True])
   print(ns_df_sorted)
  </code></pre>
  
  <p>This gives an output like this </p>
  
  <pre><code>  Feat_names   F_Scores
  4     go_out  29.870218
  8     fun1_2  27.374212
  6     fun1_1  26.470766
  3       date  25.035227
  7    shar1_1  17.629153
  2    imprace  11.331197
  0      order  11.290014
  5    sinc1_1   8.309805
  9    shar1_2   5.009775
  1   field_cd   4.515538
  </code></pre>
  
  <p>I am not sure what the F score here signifies and what I can interpret from it.</p>