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You will need to implement at least two Matlab functions: HW3main.m and svmTrain.m. The implementation details are as follows:
function [alpha] = svmTrain(X,T,kernel,C,sigma)% alpha: a solution vector for SVM.% X: training input vectors.% T: training targets.% kernel: a type of kernel function, either linear, or rbf.% C: the margin parameter.% sigma: the rbf kernel parameter.
HW3main.m implements reading in the data files, calling svmTrain.m, pre- dicting and plotting.
Test your implementation using datasets provided at the class web site. In the datasets, the first two columns represent the input vector and the last column is for the class label.
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Function Name: voteCounter Inputs (1): - (char) filename of votes Outputs (0): - none Function Description: You use the brand new VoteMaster 3000 to tally up votes in the r
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