Gini Index (or Gini Impurity) is a measure used in Decision Trees (CART algorithm) to
decide how to split the data at each node.
�� It tells how impure or mixed a node is.
Lower Gini value → purer node
Higher Gini value → more impure node
2️⃣ Where is Gini Index Used?
Used in CART (Classification and Regression Trees)
Mainly for classification problems
CART always creates binary splits
Gini Index Formula
�� General Formula

Where:
- = probability of class in node
- = number of classes
�� Binary Classification Formula

Where:
- = probability of Yes
- = probability of No
4️⃣ Gini Index of a Split (Very Important)
When a node is split into child nodes:

Where:
- = parent node
- = child nodes
- = samples in child
- = total samples
