Optimal Support Vector Selection for Kernel Perceptrons

author: Daniel García, Universidad Autónoma de Madrid

Categories

Top: Computer Science: Machine Learning: Kernel Methods: Support Vector Machines

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*Slides*
0:00	Optimal Support Vector Selection for Kernel Perceptrons
0:15	Objectives
0:54	Support Vector Machines
1:51	Convex Hull Norm Minimization
2:47	Schlesinger-Kozinec (SK) Algorithm
3:55	Kernel SK I
4:40	Kernel SK II
5:08	Kernel SK III
5:57	Support vector selection I
6:28	Support vector selection II
7:27	Support Vector Removal Method
8:33	Numerical Experiments I
9:06	Numerical Experiments II
9:38	Numerical Experiments III
10:50	Results
11:23	Heart Disease Results
12:02	Wisconsin Breast Cancer Results
12:31	Ionosphere Results
12:51	Pima Indian Diabetes Results
13:28	Heart Disease Evolution
14:04	Wisconsin Breast Cancer Disease Evolution
14:20	Ionosphere Evolution
14:56	Pima Indian Diabetes Evolution
15:12	Conclusions

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