人工智能教学资料 6ai Classification part4.pdfVIP

Artificial Intelligence Classification Yanghui Rao Assistant Prof., Ph.D School of Mobile Information Engineering, Sun Yat-sen University Artificial Intelligence: Classification Support Vector Machine ? SVM is a classifier derived from statistical learning theory by Vapnik and Chervonenkis ? Initially popularized in the Neural Information Processing Systems (NIPS) community, now an important and active field of all Machine Learning research. ? Vapnik Chervonenkis theory Artificial Intelligence: Classification Support Vector Machine ? SVMs are learning systems that ? use a hypothesis space of linear functions ? in a high dimensional feature space — Kernel function ? trained with a learning algorithm from optimization theory — Lagrange ? Implements a learning bias derived from statistical learning theory — Generalisation SVM is a classifier derived from statistical learning theory by Vapnik and Chervonenkis Artificial Intelligence: Classification denotes +1 denotes -1 f x f(x; w) = sign(wTx) How would you classify this data? Linear Classifiers Artificial Intelligence: Classification denotes +1 denotes -1 How would you classify this data? Linear Classifiers Artificial Intelligence: Classification denotes +1 denotes -1 How would you classify this data? Linear Classifiers Artificial Intelligence: Classification denotes +1 denotes -1 How would you classify this data? Linear Classifiers Artificial Intelligence: Classification denotes +1 denotes -1 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 Maximum Margin Artificial Intelligence: Classification Maximum Margin ? The geometric margin of the separator ? In order to find the maximum , we must find the minimum ? subject to (s.t.) ? Examples closest to the hyperplane are support vectors. T T1 1 2 ? ? ?? ? ? ? ?? ? ? ? w x w x w w w ? ? ? ? ? ? ? ? w? T( ) 1 0, 1,2,...,i iy i n? ? ?w x? ? Artificial Intelligence: Clas