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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.

Probability estimation Algorithm 2. (maximum a posteriori prob-ability). Given observed training data producing a1 observed ”heads,” and a0 observed ”tails,” plus prior information expressed by introduc-ing g1 imaginary ”heads” and g0 imaginary ”tails,” output the estimate qˆ = …

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