Node impurity - PowerPoint PPT Presentation

Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation

Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation. Lecture Notes for Chapter 3. Why Data Mining. Credit ratings/targeted marketing : Given a database of 100,000 names, which persons are the least likely to default on their credit cards?

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Split Selection for Decision Tree

Split Selection for Decision Tree. We already learned on selection method Information Gain (entropy) Are there any other selection criterion? Yes How many are they? A Lot Intuition Formalism Various Selection Methods. How to determine the Best Split. Greedy approach:

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