title: TypeError: fit() missing 1 required positional argument: 'y'
body: <p>I am trying to predict economic cycles using Gaussian Naive Bayes "Classifier". </p>
  
  <p>data (input X) :</p>
  
  <pre><code>             SPY    Interest Rate    Unemployment   Employment  CPI
  Date                    
  1997-01-02   56.05     7.82            9.7           3399.9     159.100
  1997-02-03   56.58     7.65            9.8           3402.8     159.600
  1997-03-03   54.09     7.90            9.9           3414.7     160.000
  </code></pre>
  
  <p>target (output Y) :</p>
  
  <pre><code>    Economy
  0   Expansion
  1   Expansion
  2   Expansion
  3   Expansion
  </code></pre>
  
  <p>Below is my code:</p>
  
  <pre><code>from sklearn.naive_bayes import GaussianNB
  from sklearn import metrics
  from sklearn.cross_validation import train_test_split
  X = data
  Y = target
  model = GaussianNB
  X_train, X_test, Y_train, Y_test = train_test_split(X,Y)
  model.fit(X_train, Y_train)
  </code></pre>
  
  <p>Below is Error:</p>
  
  <pre><code>TypeError                                 Traceback (most recent call last)
  &lt;ipython-input-132-b0975752a19f&gt; in &lt;module&gt;()
    6 model = GaussianNB
    7 X_train, X_test, Y_train, Y_test = train_test_split(X,Y)
    ----&gt; 8 model.fit(X_train, Y_train)
  
    TypeError: fit() missing 1 required positional argument: 'y'
  </code></pre>
  
  <p>What am I doing wrong? How can I resolve this issue /error ?</p>