title: How to use sklearn ( chi-square or ANOVA) to removes redundant features
body: <p>Under feature selection step we want to identify relevant features and remove redundant features.</p>
  
  <p>From my understanding redundant features are depended features. (so we want to leave only independent features between features to them self)</p>
  
  <p>My question is about removing redundant features using <code>sklearn</code> and ANOVA / Chi-square tests.</p>
  
  <p>From what I read (and saw examples) we are using <code>SelectKBest</code> or <code>SelectPercentile</code> to leave best features which are depended with the target (<code>y</code>)</p>
  
  <p>But can we use those methods with <code>chi2, f_classif</code> in order to remove depended features ?</p>
  
  <p>In other words, I want to remove redundant features with sklearn methods. How can we do it ?</p>