What does the Gini impurity measure in a Decision Tree?
Practice Questions
Q1
What does the Gini impurity measure in a Decision Tree?
The accuracy of the model.
The likelihood of misclassifying a randomly chosen element.
The depth of the tree.
The number of features used.
Questions & Step-by-Step Solutions
What does the Gini impurity measure in a Decision Tree?
Step 1: Understand that Gini impurity is a way to measure how mixed the classes are in a dataset.
Step 2: Realize that a lower Gini impurity means the classes are more pure (less mixed), while a higher Gini impurity means the classes are more mixed.
Step 3: Know that Gini impurity helps in decision trees by showing how likely it is to misclassify a randomly chosen item from the dataset.
Step 4: Use Gini impurity to find the best way to split the data into groups that are more similar to each other.
