/DecisionTreeModelling

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

Primary LanguagePython

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
  1. 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)