Complete Guide To Naive Bayes Classifier
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SOLVED: Consider a classification setting with classes and a predictor. When using the Bayes classifier, we assign an observation to the class that has the highest conditional probability, denoted as Pr(Y = k|X = x). The Bayes decision boundary is such that Pr(Y = i|X = x) = Pr(Y = j|X = x), where i and j are different classes. It represents the values of the variable for which we have equal probability. With LDA (Linear Discriminant Analysis), we can find the Bayes decision boundary using the L
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