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Statistical Learning Theory
Published on Feb 25, 200731629 Views
This course will give a detailed introduction to learning theory with a focus on the classification problem. It will be shown how to obtain (pobabilistic) bounds on the generalization error for certai
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Chapter list
Statistical Learning Theory00:01
Roadmap (1)00:35
Roadmap (2)02:21
Lecture 102:49
Learning and Inference03:28
Pattern recognition04:51
Approximation/Interpolation06:09
Occam’s Razor08:48
No Free Lunch10:52
Assumptions13:34
Goals14:28
Probabilistic Model15:39
Probabilistic Model17:56
Probabilistic Model19:43
Target function23:26
Assumptions about P29:34
Approximation/Interpolation (again)32:41
Overfitting/Underfitting33:10
Empirical Risk Minimization34:03
Approximation/Estimation35:25
Structural Risk Minimization38:13
Regularization40:15
Bounds (1)41:41
Bounds (2)42:42