TypeError: fit() missing 1 required positional argument: 'y'
<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>