title: Trying to use fit with SelectKBest variable and keep getting a TypeError
body: <p>I'm trying to use .fit() on my SelectKBest variable and I keep getting an error once my program hits skb.fit(X, y). Not sure why.</p>
  
  <p>Error I'm getting:
  <strong>fit % (self.score_func, type(self.score_func)) TypeError: The score function should be a callable, 26.48914983923762 (&lt; class 'numpy.float64' >) was passed.</strong></p>
  
  <p>My Code:</p>
  
  <pre><code>X = df.loc[:, features].astype(float)
  y = df.iloc[:, 0].astype(float)
  
  model = LogisticRegression()
  classifier = LogisticRegression()
  skb = SelectKBest(score_func = chi2, k = 3)
  
  skb.fit(X, y) # Error happens here
  </code></pre>
  
  <p>What my Dataframe looks like:</p>
  
  <pre><code>         col1  col2   col3      col4   col5 col6    col7
  0           0  22.0   7.2500       3      1  1.0      0
  1           1  38.0  71.2833       1      1  0.0      0
  2           1  26.0   7.9250       3      0  0.0      0
  3           1  35.0  53.1000       1      1  0.0      0
  4           0  35.0   8.0500       3      0  1.0      0
  ..        ...   ...      ...     ...    ...  ...    ...
  885         0  39.0  29.1250       3      0  0.0      5
  886         0  27.0  13.0000       2      0  1.0      0
  887         1  19.0  30.0000       1      0  0.0      0
  889         1  26.0  30.0000       1      0  1.0      0
  890         0  32.0   7.7500       3      0  1.0      0
  </code></pre>
  
  <p>I tried changing each col to a float</p>
  
  <p><strong>Edit</strong>: I added a comment on the line where the error happens</p>