The posterior probabilities of four hypothesis h1,h2,h3,h4 are
(0.2, 0.5,0.2, 0.1) respectively. A new training sample...
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The posterior probabilities of four hypothesis h1,h2,h3,h4 are(0.2, 0.5,0.2, 0.1) respectively. A new training sample isclassified +ve by h2 and h3, while h1 and h4 classify the same datainstance as -ve. Find the classification with Bayes OptimalClassifier and Brute Force Classification?
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The naive bayes classifier treats every attribute independently It will sum up the weightage of the classifiers which identified the tuple as ve and ve separately and compare
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