More Related Content Similar to Support Vector Machines Similar to Support Vector Machines (20) Support Vector Machines5. Linear Classifiers y est denotes +1 denotes -1 How would you classify this data? Copyright © 2001, 2003, Andrew W. Moore f x f ( x , w ,b ) = sign( w . x - b ) 6. Linear Classifiers f x y est denotes +1 denotes -1 f ( x , w ,b ) = sign( w . x - b ) How would you classify this data? Copyright © 2001, 2003, Andrew W. Moore 7. Linear Classifiers f x y est denotes +1 denotes -1 f ( x , w ,b ) = sign( w . x - b ) How would you classify this data? Copyright © 2001, 2003, Andrew W. Moore 8. Linear Classifiers f x y est denotes +1 denotes -1 f ( x , w ,b ) = sign( w . x - b ) How would you classify this data? Copyright © 2001, 2003, Andrew W. Moore 9. Linear Classifiers f x y est denotes +1 denotes -1 f ( x , w ,b ) = sign( w . x - b ) How would you classify this data? Copyright © 2001, 2003, Andrew W. Moore 10. Maximum Margin f x y est denotes +1 denotes -1 f ( x , w ,b ) = sign( w . x - b ) The maximum margin linear classifier is the linear classifier with the maximum margin. This is the simplest kind of SVM (Called an LSVM) Linear SVM Copyright © 2001, 2003, Andrew W. Moore 40. Text Categorization Inductive learning Inpute : Output : f(x) = confidence(class) In the case of text classification ,the attribute are words in the document ,and the classes are the categories.