In Decision Trees, what does the Gini impurity measure?

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Question: In Decision Trees, what does the Gini impurity measure?

Options:

Correct Answer: The purity of a node

Solution:

Gini impurity measures the impurity or disorder of a node, helping to determine the best split at each node.

In Decision Trees, what does the Gini impurity measure?

In Decision Trees, what does the Gini impurity measure?

Step 1: Understand that a Decision Tree is a way to make decisions based on data.
Step 2: Know that each point in the tree is called a 'node'.
Step 3: Realize that nodes can have different categories or classes (like 'yes' or 'no').
Step 4: Gini impurity is a number that tells us how mixed the classes are at a node.
Step 5: A Gini impurity of 0 means all items in the node belong to one class (pure).
Step 6: A higher Gini impurity means the classes are mixed (impure).
Step 7: We use Gini impurity to find the best way to split the data at each node to make it more pure.

Gini Impurity – A metric used in decision trees to quantify the impurity or disorder of a node, indicating how mixed the classes are.