Linear classifiers X f est f( w, b= sign (w x-b denotes +1 denotes -1 How would you classify this data? Copyright 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 6
Copyright © 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 6 Linear Classifiers f x a y est denotes +1 denotes -1 f(x,w,b) = sign(w. x - b) How would you classify this data?
Linear classifiers X f est f( w, b=sign ( w x-b denotes +1 denotes -1 How would you classify this data? Copyright 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 7
Copyright © 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 7 Linear Classifiers f x a y est denotes +1 denotes -1 f(x,w,b) = sign(w. x - b) How would you classify this data?
Linear classifiers X f est f y, b)=sign(w, X-b denotes +1 denotes -1 Any of these would be fine but which is best? Copyright 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 8
Copyright © 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 8 Linear Classifiers f x a y est denotes +1 denotes -1 f(x,w,b) = sign(w. x - b) Any of these would be fine.. ..but which is best?
Classifier Margin f est f( w, b=sign ( w x-b denotes +1 denotes -1 Define the margin of a linear classifier as the Width that the boundary could be increased by before hitting datapoint Copyright o 2001, 2003, Andrew W.Modre Support Vector Machines: Slide 9
Copyright © 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 9 Classifier Margin f x a y est denotes +1 denotes -1 f(x,w,b) = sign(w. x - b) Define the margin of a linear classifier as the width that the boundary could be increased by before hitting a datapoint
Maximum Margin f est f( w, b=sign w x-b) denotes +1 denotes -1 The maximum margin linear classifier is the linear classifier With the, um maximum margin This is the simplest kind of SVM(Called an SVM Linear sⅥM Copyright 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 10
Copyright © 2001, 2003, Andrew W. Moore Support Vector Machines: Slide 10 Maximum Margin f x a 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, um, maximum margin. This is the simplest kind of SVM (Called an LSVM) Linear SVM