Gini Index and Entropy|Gini Index and Information gain in Decision Tree|Decision tree splitting rule

Published: 01 January 1970
on channel: Coder's Digest

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#giniindex #ginigain #decisiontree
today we will discuss how does a decision tree split or you can say how to split a tree. we will discuss the process to calculate gini coefficient, gini index and entropy etc.
basically a decision tree split the tree based on a variable with gives the maximum information gain also known as gini gain.
Gini impurity - any node which contains only one class will be called as homogeneous or perfectly pure node and hence will provide a gini coefficient of 0.

what we will discuss in this video :
How does a decision tree work? A Decision Tree data into small subsets based on the value of each variable. Splitting stops when every subset is pure .
This video explains Gini and Entropy with example.
Below questions are answered in this video:
1.What is Gini Index?
2.What is Information gain?
3.What is Entropy?
4.What is tree splitting criteria?
5.How to split decision tree?

Thanks