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.
machine learning algorithms. In this simple example you have a coin, represented by the random variable X. If you flip this coin, it may turn up heads (indicated by X =1) or tails (X =0). The learning task is to estimate the probability that it will turn up heads; that is, to estimate P(X=1).
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