Extra Credit (for an additional 20 points): – Use your priorimplementation of k-means to find prototypes to act as proxy examplesin k-nearest neighbor. Note that the k for k-means need not be thesame as the k for k-nearest neighbor. Be sure to tune to find theproper number of clusters. You will use this on both theclassification and the regression problems. – Implement a radial basisfunction neural network using one hidden node for each data point froma random sample of 10% of the training set. – Implement the radialbasis function neural network using the results of k-means clusteringfor the hidden nodes. You may use the results of clustering forprototypes here.
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[Solved] Extra Credit Programming Project #3
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File Name: Extra_Credit_Programming_Project_#3.zip
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