Explain the steps in making a decision tree in data science?

Data Science, AI and ML
#1
  1. Take the entire data set as input
  2. Calculate entropy of the target variable, as well as the predictor attributes
  3. Calculate your information gain of all attributes (we gain information on sorting different objects from each other)
  4. Choose the attribute with the highest information gain as the root node
  5. Repeat the same procedure on every branch until the decision node of each branch is finalized

For example, let’s say you want to build a decision tree to decide whether you should accept or decline a job offer. The decision tree for this case is as shown:

It is clear from the decision tree that an offer is accepted if:

  • Salary is greater than $50,000
  • The commute is less than an hour
  • Incentives are offered