title: Why isn't model tuning done before model selection?
body: <p>I have observed in many articles and books that model selection is done before model tuning.</p>
  
  <p>Model selection is generally done using some form of cross validation like k-fold where multiple models' metrics are calculated and the best one is selected.</p>
  
  <p>And then the model selected is tuned to get the best hyperparameters. </p>
  
  <p>But my question is that a model that was not selected might perform better with the right hyperparameters. </p>
  
  <p>So why aren't all the models we are interested in tuned to get the right hyperparameters and then the best model be selected by cross validation.</p>