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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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Complete assignment as per attached word doc. Include function files along with Matlab assignment file.
In MATLAB, create a correlation matrix for all of the variables in the data (it should be an 8x8 matrix). To do this you will have to convert the "southern"variable into a number.
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