recitation-SVM - Recitation 10-701/15-781, Fall 2008 SVM By...

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Recitation 10-701/15-781, Fall 2008 SVM By Hanghang Tong (htong@cs) Some Parts of the slides are from previous years’ recitation and lecture notes 1
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Roadmap Hinge Loss How to derive? What is the intuition SVM vs. LR vs. AdaBoost SMO How does it work Implications of SMO Limitations of SMO SVR 2
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Hinge Loss (from HW2) We know (soft-margin linear SVM) Want to show 3 ?
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Hinge Loss (from HW2) We know (soft-margin linear SVM) Want to show 4 max(0,1 ( )) t i i i y w x b  But… ( )) t i i i y w x b  i=
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Hinge Loss: What is the intuition? 5 ii yf Loss function ( ) ( ) i t y f w x b H x sign f  : true label
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Hinge Loss: What is the intuition? 6 ii yf Loss function ( ) ( ) i t y f w x b H x sign f  : true label Ideal Case Wrong Correct but less confident Correct & Confident
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Hinge Loss: What is the intuition? 7 ii yf Loss function ( ) ( ) i t y f w x b H x sign f  : true label But, non-convex Wrong Correct but less confident Correct & Confident
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Hinge Loss: What is the intuition?
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This note was uploaded on 01/26/2010 for the course MACHINE LE 10701 taught by Professor Ericp.xing during the Fall '08 term at Carnegie Mellon.

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recitation-SVM - Recitation 10-701/15-781, Fall 2008 SVM By...

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