kruthi-mahesh / DecisionTreeModelling

To build a decision tree and predict the result for the input for any dataset.

Decision tree modelling

Based upon entropy-information gain method

Building of Decision Tree upon any training dataset(Generic DT).

Examples handled here

1. Predicting whether a user is likely to subscribe based upon

• Attributes
  • Company Name (Categorial)
  • Country (Categorial)
  • Viewed FAQ (Binary)
  • No. of times Viewed (Continuous)
• Class(Result)
  • None
  • Basic
  • Premium

2. Predicting whether a Borrower is likely to pay the Loan or Not(Defaulted Borrower)

• Attributes
  • Owns A Home (Binary)
  • Marital Status (Categorial)
  • Annual Income (Continuous)
• Class
  • yes (Defaulted Borrower)
  • no (Not a Defaulted Borrower)