title: How to decide to convert to categorical variable or keep it numeric?
body: <p>This might be a basic or trivial question and might be straightforward. Still I would like to ask this to clear my doubt once and for all.</p>
  
  <p>Take example of Passanger Class in Famous Titanic Data. Functionally it is indeed a Categorical Data, so it will make perfect sense to convert it to categorical variable. Algorithms as per my understanding tend to see a pattern specific to that class. But at the same time if you see it as numeric variable, it might denote a range also for a decision tree. Say passangers in between first class and second class. </p>
  
  <p>It looks both are correct and both will affect the machine learning algorithm outputs in different ways.</p>
  
  <p>Which one is appropriate and is there anywhere there is a extensive discussion about it? Should we use such ambiguous variables as numeric as well its copy as a categorical variable, which might prove to be a technique to uncover more patterns?</p>