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information gain

AI, ML & GenAI interview questions tagged information gain, across every topic.

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Concepts behind "information gain"

The curriculum that explains the ideas these questions test.

Foundational
📊 Evaluation & ML Foundations
Decision Trees and Splitting CriteriaA decision tree recursively splits the feature space by choosing the split that most reduces impurity (Gini or entropy), producing a flowchart you can read top to bottom. Interviews probe trees because they reveal whether you understand impurity-based splitting, why depth is the bias-variance knob, and how a single high-variance tree becomes the building block for random forests and gradient boosting.
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