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Explain the steps in making a decision tree.

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Take the entire data set as input

  1. Calculate entropy of the target variable, as well as the predictor attributes
  2. Calculate your information gain of all attributes (we gain information on sorting different objects from each other)
  3. Choose the attribute with the highest information gain as the root node 
  4. Repeat the same procedure on every branch until the decision node of each branch is finalized
  5. For example, let's say you want to build a decision tree to decide whether you should accept or decline a job offer. 

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