Non Linear SVM and Kernal function
Non-Linear SVM and Kernal function Non Linear Data : If a data set or given sample can not be separated by a single line then it is non linear data. Non Linear SVM: To separate non linear data , non linear SVM is used. Trick Kernel Function: To separate non linear data Trick Kernals are used. Both non linear data and Trick Kernals are related to each other. Non Linear Data: Figure 2 shows non linear data. Single line or straight line can not separate these data. Straight line gives less than 50% accuracy. Figure1: Non Linear Data Solution to this problem is use of Trick Kernel. Trick Kernel takes input low dimensional feature space and convert into high dimensional feature space so that non separable data get separated Two dimensional data converted into three dimensional data using kernel as shown in figure 1 and it become seperable. · Following are the different kernel used in SVM: Ø ...



























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