hw3 - CS 6375 Machine Learning Fall 2010 Assignment 3:...

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CS 6375 Machine Learning Fall 2010 Assignment 3: Bayesian Learning and Neural Networks Part I: Due by Sunday, October 17, 11:59 p.m. Extra Credit: Due by Sunday, October 24, 11:59 p.m. Part II: Due by Sunday, October 31, 11:59 p.m. Submission instructions for the written problems: Slip a hard-copy solution under Eduardo’s office door or submit your solution electronically via eLearning. If you choose to submit electronically, submit your solution as a single PDF file. Regardless of the submission method you use, make sure that your name appears at the beginning of your submission. Whenever possible, you should provide brief justifications for your solution. Part I: Bayesian Learning (55 points) 1. Bayesian Classifiers (10 points) Shyam is a CS 6375 student. Recently, his mood has been highly influenced by three factors: the weather (W), his study habits (S), and whether his neighbor is at home or not (N). We want to predict his happiness according to these three factors using previous observations. The table below shows this data. Weather (W) Study (S) Neighbor (N) Happy (H) Bad Fail Home No Good Fail Out No Good Fail Out No Good Fail Out No Bad Pass Home No Bad Pass Home Yes Bad Pass Home Yes Good Pass Out Yes (a) (5 pts) On a new day when W=Good, S=Pass, and N=Out, how would we predict his happiness using a Naive Bayes classifier? Show your calculations. (b) (5 pts) On the day when W=Good, S=Pass, and N=Out, how would we predict his happiness using a Bayes classifier instead? Show your calculations. 2. Naive Bayes Reasoning (15 points) Below are some statistics on the usage of programming languages in software companies: 50% of all programmers can program in C++. 1
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40% of all programmers can program in Java. 1% of all programmers work for Macrosoft, the largest software company. 99% of Macrosoft employees can program in C++. 98% of Macrosoft employees can program in Java. Using Naive Bayes reasoning, decide if a programmer who knows both C++ and Java is a Macrosoft employee. Show your calculations. 3. Probability I (10 points) Suppose we have two random variables, both defined over all students in CS 6375. wh
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This note was uploaded on 11/03/2010 for the course COMPUTER S CS6375 taught by Professor Vincentng during the Fall '10 term at University of Texas at Dallas, Richardson.

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hw3 - CS 6375 Machine Learning Fall 2010 Assignment 3:...

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