title: Logistic Regression Scikit-Learn Getting the coefficients of the classification
body: <p>I am doing Multiclass Classification and applying Logistic regression on it</p>
  
  <p>When i fitted the data by calling</p>
  
  <pre><code>logistic.fit(InputDATA,OutputDATA)
  </code></pre>
  
  <p>the estimator "logistic " fits the data.</p>
  
  <p>Now when I call <code>logistic.coef_</code> it prints a 2D array
  with 4 rows(I HAD FOUR CLASSES) and n columns(one for each feature)</p>
  
  <p>THIS IS WHAT I SAW ON SCIKIT LEARN SITE:</p>
  
  <blockquote>
    <p>coef_ : array, shape (n_features, ) or (n_targets, n_features)
    Estimated coefficients for the linear regression problem. If multiple
    targets are passed during the fit (y 2D), this is a 2D array of shape
    (n_targets, n_features), while if only one target is passed, this is a
    1D array of length n_features.</p>
  </blockquote>
  
  <p>Now my query is :
  Why different coefficients are there for different classes as i need only one hypothesis which would predict the output.</p>