title: Remove noisy and redundant features
body: <p>I have extracted features from a video sequence based on facial markers as means and standard deviations of those markers over a video sequence. They need to be classified into four different classes based on those markers.</p>
  
  <p>In all I have a feature set of around 260 features. How should I determine which features are noisy and redundant in my set. I read about it in some research papers and some of them used the plus l take away r algorithm that I found to be quite appropriate but in such algorithms they always rate one feature against the other and say its good or bad compared to it. 
  How do I rate my features to be good or bad? What criterion are used for that generally?</p>
  
  <p>I researched a lot for a couple of days but found nothing clear cut and useful. Would be grateful for the help, Thanks.</p>