Entropy & Gini: How Mixed Is a Node?
This lesson is part of the course
In this lesson
You count the defaults in Kestrel Lending's 20 past loans and measure how mixed the group is with entropy (in bits) and Gini impurity, the two scores every decision tree uses.
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Lessons in this course
- Entropy & Gini: How Mixed Is a Node? Locked
- Information Gain: Scoring Candidate Splits with COUNTIFS Locked
- The Best Numeric Threshold: Trying Every Cut-Point Locked
- Growing a Two-Level Tree: Leaves & Nested IF Predictions Locked
- Overfitting & Pruning: Train vs Test Accuracy by Depth Locked
- Bagging & Random Forests: Majority Vote and Out-of-Bag Rows Locked
- Gradient Boosting by Hand: Residuals, Stumps & a Learning Rate Locked
- Feature Importance from Impurity Decrease Locked