The Gini Index

The Gini Index is a measure used in decision trees to evaluate how well a split separates different classes or groups in a dataset. It ranges from 0 to 1, where 0 indicates perfect separation (all items in a group belong to the same class), and 1 indicates maximum mixing of classes. When building decision trees for tasks like classification, the goal is to choose splits that reduce the Gini Index, leading to more homogeneous groups. Essentially, it helps identify splits that best distinguish between different categories, improving the accuracy and effectiveness of the decision-making process.