What does the Gini impurity measure in Decision Trees?
Practice Questions
Q1
What does the Gini impurity measure in Decision Trees?
The accuracy of the model.
The purity of a node in the tree.
The depth of the tree.
The number of features used.
Questions & Step-by-Step Solutions
What does the Gini impurity measure in Decision Trees?
Step 1: Understand that Gini impurity is a way to measure how mixed or pure a group of items is.
Step 2: In a Decision Tree, each node represents a group of items (like fruits or animals).
Step 3: Gini impurity calculates how often a randomly chosen item from the group would be incorrectly labeled if it was randomly labeled according to the distribution of labels in the group.
Step 4: A Gini impurity of 0 means all items in the group are the same (pure), while a higher value means the group is mixed (impure).
Step 5: Decision Trees use Gini impurity to decide the best way to split the group into smaller groups, aiming for more pure groups.
