title: Setting feature weights for KNN
body: <p>I am working with sklearn's implementation of KNN. While my input data has about 20 features, I believe some of the features are more important than others. Is there a way to: </p>
  
  <ol>
  <li>set the feature weights for each feature when "training" the KNN learner.  </li>
  <li>learn what the optimal weight values are with or without pre-processing the data.  </li>
  </ol>
  
  <p>On a related note, I understand generally KNN does not require training but since sklearn implements it using KDTrees, the tree must be generated from the training data. However, this sounds like its turning KNN into a binary tree problem. Is that the case?</p>
  
  <p>Thanks.</p>