hw4 - CS 6375 Machine Learning Fall 2010 Assignment 4:...

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CS 6375 Machine Learning Fall 2010 Assignment 4: Neural Networks, MLE, and Instance-Based Learning Part I: Due by Tuesday, November 9, 11:59 p.m. Part II: Due by Monday, November 15, 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: Programming (40 points) Implement the gradient descent algorithm that we discussed in class to train a sigmoid unit for binary classification tasks (i.e. each instance will have a class value of 0 or 1). To simplify the im- plementation, you may assume that all attributes are binary-valued (i.e. the only possible attribute values are 0 and 1) and that there are no missing values in the training or test data. Sample training files ( train2.dat , train5.dat ) and test files ( test2.dat , test5.dat ) are available from the assignment page of the course website. In these files, only lines containing non-space characters are relevant. The first relevant line holds the attribute names. Each following relevant line defines a single example. Each column holds this example’s value for the attribute named at the head of the column. The last column (labeled “class”) holds the class label for the examples. When applying the trained sigmoid unit to a test instance, use 0.5 as the classification threshold (i.e., classify the instance as 1 if the unit outputs a value that is at least 0.5; otherwise classify the instance as 0). IMPORTANT: To implement the perceptron learning algorithm, you may use C, C++, Python, Java, or any programming languages pre-approved by your dear TA, Eduardo Blanco. If you have any doubts, just ask Eduardo ( [email protected] ). Your program should be able to handle
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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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hw4 - CS 6375 Machine Learning Fall 2010 Assignment 4:...

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