Lecture outline. Classification Naïve Bayes c lassifier Nearest-neighbor classifier. Eager vs Lazy learners. Eager learners: learn the model as soon as the training data becomes available Lazy learners: delay model-building until testing data needs to be classified
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k-nearest neighbors of a record x are data points that have the k smallest distance to x
Pr(Y|X) : Posterior probability
Pr(Y): Prior probability
X’=(Home Owner=No, Marital Status=Married, AnnualIncome=120K)
Compute: Pr(Yes|X’), Pr(No|X’) pick No or Yes with max Prob.
How can we compute these probabilities??