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CMU CS 10701 - Algorithm
School name Carnegie Mellon University
Course Cs 10701- Introduction to Machine Learning
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Xi Chen based on the notes from Ajit Expectation Maximization EM is a technique used in point estimation Given a set of observable variables X and unknown latent variables Z we want to estimate parameters in a model E step Evaluation M step Evaluation Binomial Mixture Model You have two coins with unknown probabilities of heads denoted p and q respectively The first coin is chosen with probability and the second coin is chosen with probability 1 The chosen coin is flipped once and the result is recorded x 1 1 0 1 0 0 1 0 0 0 1 1 Heads 1 Tails 0 Hidden Variables Zi 1 the coin tossed with the head probability p Zi 0 the coin tossed with the head probability q Parameters p q E step Evaluation M step

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CMU CS 10701 - Algorithm

School: Carnegie Mellon University
Course: Cs 10701- Introduction to Machine Learning
Pages: 5
Documents in this Course
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