Welcome to the session ‘Algorithms for Decision Tree Construction’. In the previous session, you learnt about the underlying concepts of decision trees and their interpretation. You also learnt how to construct a decision tree. You learnt about the advantages of decision trees and also understood how they help in solving the regression problems that cannot be handled by linear regression. In this session, you will learn about the methods for decision tree construction.
In this session:
- Splitting and homogeneity.
- Impurity measures.
- Best split
- Regression trees
Guidelines for in-module questions
In-video and in-content questions are not graded.
People you will hear from in this session
Subject Matter Expert
Analytics Lead, Flipkart