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# review_4perPage - Outline More Handling Missing Data Data...

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More Handling Missing Data Data Mining Prof. Dawn Woodard School of ORIE Cornell University 1 Outline 1 Announcements 2 Practice Question 3 Handling Missing Data 2 Announcements Questions? 4 Error Rates Say we have a classiFer that, if X 1 = 0, ﬂips a biased coin; with probability p 0 the coin is heads. If the coin is heads we predict Y = 1; otherwise, we predict Y = 0. If X 1 = 1, we ﬂip a different biased coin; with probability p 1 the coin is heads. If this coin is heads we predict Y = 1, and otherwise we predict Y = 0. Say that Pr ( X 1 = 1 | Y = 1 )= 0 . 3 and Pr ( X 1 = 1 | Y = 0 0 . 6. What is the false positive rate of our classiFer? What is the false negative rate? 6

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Naive Bayes Say for a different problem our training data looks like: X 1 X 2 Y a1 1 a0 0 b0 1 1 1 b1 0 ?1 1 ?0 0 0 0 1 8 Naive Bayes What are the (frequentist) estimates of Pr ( Y ) , Pr ( X 1 | Y ) , and Pr ( X 2 | Y ) for naive Bayes? X 1 X 2 Y 1 0 1 1 1 0 1 0 0 0 1 9 Naive Bayes Estimate the probability that Y = 0, given that X 1 = b and X 2 = 0.
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review_4perPage - Outline More Handling Missing Data Data...

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