title: Getting weights of features using scikit-learn Logistic Regression
body: <p>I am a little new to this. 
  I am using a simple Logistic Regression Classifier in python scikit-learn. I have 4 features. 
  My code is </p>
  
  <pre><code>X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size = 0.2, random_state = 42) 
  classifier = LogisticRegression(random_state = 0, C=100)
  classifier.fit(X_train, y_train)
  coef = classifier.coef_[0]
  print (coef)
  
  [-1.07091645 -0.07848958  0.66913624  0.43500273]
  </code></pre>
  
  <ul>
  <li>I want to know what does the coef array signifies? </li>
  <li>can we use these coef * features to rank?</li>
  <li>Does this mean that the last two features are most important in classifying results?</li>
  </ul>