A machine learning approach for acquiring descriptive classification rules of shape contours

decision tree: a traditional learning model that realizes conditional aggregation.. Disclaimers about Decision

• validation set blending: a special any blending model E test (squared): 519.45 =⇒ 456.24. —helped secure the lead in last

Hsuan-Tien Lin (NTU CSIE) Machine Learning Techniques 21/25.. Gradient Boosted Decision Tree Summary of Aggregation Models. Map of

2 Combining Predictive Features: Aggregation Models Lecture 7: Blending and Bagging.. Motivation of Aggregation

Which of the following aggregation model learns diverse g t by reweighting and calculates linear vote by steepest search?.

3 Distilling Implicit Features: Extraction Models Lecture 14: Radial Basis Function Network. RBF

Lecture 4: Soft-Margin Support Vector Machine allow some margin violations ξ n while penalizing them by C; equivalent to upper-bounding α n by C Lecture 5: Kernel Logistic

Hsuan-Tien Lin (NTU CSIE) Machine Learning Techniques 5/22.. Decision Tree Decision Tree Hypothesis. Disclaimers about