title: How to find the features names of the coefficients using scikit linear regression?
body: <pre><code>#training the model
  model_1_features = ['sqft_living', 'bathrooms', 'bedrooms', 'lat', 'long']
  model_2_features = model_1_features + ['bed_bath_rooms']
  model_3_features = model_2_features + ['bedrooms_squared', 'log_sqft_living', 'lat_plus_long']
  
  model_1 = linear_model.LinearRegression()
  model_1.fit(train_data[model_1_features], train_data['price'])
  
  model_2 = linear_model.LinearRegression()
  model_2.fit(train_data[model_2_features], train_data['price'])
  
  model_3 = linear_model.LinearRegression()
  model_3.fit(train_data[model_3_features], train_data['price'])
  
  # extracting the coef
  print model_1.coef_
  print model_2.coef_
  print model_3.coef_
  </code></pre>
  
  <p>If I change the order of the features, the coef are still printed in the same order, hence I would like to know the mapping of the feature with the coeff</p>