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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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1.28k views • 82 slides

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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277 views • 27 slides

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Node impurity - PowerPoint PPT Presentation

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

Split Selection for Decision Tree