Transcription of CHAPTER 2 Estimating Probabilities
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CHAPTER 2 Estimating Probabilities
CHAPTER 2 Estimating ProbabilitiesMachine LearningCopyrightc 2017. Tom M. Mitchell. All rights reserved.*DRAFT OF January 26, 2018**PLEASE DO NOT DISTRIBUTE WITHOUT AUTHOR SPERMISSION*This is a rough draft CHAPTER intended for inclusion in the upcoming secondedition of the textbookMachine Learning, Mitchell, McGraw are welcome to use this for educational purposes, but do not duplicateor repost it on the internet. For online copies of this and other materialsrelated to this book, visit the web site send suggestions for improvements, or suggested exercises, machine learning methods depend on probabilistic approaches. Thereason is simple: when we are interested in learning some target functionf:X Y, we can more generally learn the probabilistic functionP(Y|X).By using a probabilistic approach, we can design algorithms that learn func-tions with uncertain outcomes ( , predicting tomorrow s stock price) andthat incorporate prior knowledge to guide learning ( , a bias that tomor-row s stock price is likely to be similar to today s price).
joint probabilities over any subset of the variables, given their joint distribution. This is accomplished by operating on the probabilities for the relevant rows in the table. For example, we can calculate: The probability that any single variable will take on any specific value. For example, we can calculate that the probability P(Gender ...
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