Splitting criteria - PowerPoint PPT Presentation

CS 391L: Machine Learning: Decision Tree Learning

CS 391L: Machine Learning: Decision Tree Learning. Raymond J. Mooney University of Texas at Austin. color. color. green. green. red. red. blue. blue. shape. shape. pos. C. neg. B. circle. circle. triangle. triangle. square. square. B. neg. C. neg. pos. A.

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Measures of Node Impurity

Measures of Node Impurity. Gini Index Entropy Misclassification error. M0. M2. M3. M4. M1. M12. M34. How to Find the Best Split. Before Splitting:. A?. B?. Yes. No. Yes. No. Node N1. Node N2. Node N3. Node N4. Gain = M0 – M12 vs M0 – M34 (in node impurity).

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