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4. Bayes Optimal Classifier (20 points) Suppose there are four hypothesis {h1, h2, h3, h4}. The posterior probabilities for different hypothesis are P(h1|D)=0.25, P(h2|D)=0.3, P(h3|D)=0.4,
4. Bayes Optimal Classifier (20 points) Suppose there are four hypothesis {h1, h2, h3, h4}. The posterior probabilities for different hypothesis are P(h1|D)=0.25, P(h2|D)=0.3, P(h3|D)=0.4, P(h4|D)=0.05. The set of possible classification of the new instance is V={+,-}. We also have P(- |h1)=0, P(+|h1)=1, P(-|h2)=1, P(+|h2)=0, P(-|h3)=1, P(+|h3)=0, P(-|h4)=1 and P(+|h4)=0. What is the result from Bayes optimal classifier?
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