Question: Problem 6. (10 points) Consider the problem of training a classifier on a training set compris- ing two linearly separable classes. Explain why maximizing the

Problem 6. (10 points) Consider the problem of

Problem 6. (10 points) Consider the problem of training a classifier on a training set compris- ing two linearly separable classes. Explain why maximizing the margin using a Support Vector Machine is a better option than (a) minimizing the number of misclassified samples using a Perceptron (5 points) (b) training a classifier using Maximum Likelihood Estimation and modeling the classes as multi-variate Gaussian distributions (5 points) Problem 6. (10 points) Consider the problem of training a classifier on a training set compris- ing two linearly separable classes. Explain why maximizing the margin using a Support Vector Machine is a better option than (a) minimizing the number of misclassified samples using a Perceptron (5 points) (b) training a classifier using Maximum Likelihood Estimation and modeling the classes as multi-variate Gaussian distributions (5 points)

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