title: Scikit-Learn Linear Regression how to get coefficient's respective features?
body: <p>I'm trying to perform feature selection by evaluating my regressions coefficient outputs, and select the features with the highest magnitude coefficients. The problem is, I don't know how to get the respective features, as only coefficients are returned form the coef._ attribute. The documentation says:</p>
  
  <blockquote>
    <p>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>I am passing into my regression.fit(A,B), where A is a 2-D array, with tfidf value for each feature in a document. Example format:</p>
  
  <pre><code>         "feature1"   "feature2"
  "Doc1"    .44          .22
  "Doc2"    .11          .6
  "Doc3"    .22          .2
  </code></pre>
  
  <p>B are my target values for the data, which are just numbers 1-100 associated with each document:</p>
  
  <pre><code>"Doc1"    50
  "Doc2"    11
  "Doc3"    99
  </code></pre>
  
  <p>Using regression.coef_, I get a list of coefficients, but not their corresponding features! How can I get the features? I'm guessing I need to modfy the structure of my B targets, but I don't know how.</p>