COSC 575: Machine Learning

Project 3
Spring 2012

Due: Thu, Mar 22 @ 11:59 P.M.
10 points

Choose one of the following:

The implementation must be general. Implement the learner as a single executable. No windows. No menus. No prompts. Just do it.

The logic of the implementation should be the same as that for the implementations of p2. If the user runs a learner and specifies only a training set, then the program should evaluate using 10-fold cross-validation and output the results. Naturally, the user can use the -x switch to change the default. Otherwise, if the user specifies both a training and testing set, then the program should build a model from the training set, evaluate it on the testing set, and output the results.

Instructions for Submission

In the header comments in at least the main file of your project, provide the following information:
//
// Name
// E-mail Address
// Platform: Windows, MacOS, Linux, Solaris, etc.
// Language/Environment: gcc, g++, java, g77, ruby, python, haskell, etc.
//
// In accordance with the class policies and Georgetown's Honor Code,
// I certify that, with the exceptions of the class resources and those
// items noted below, I have neither given nor received any assistance
// on this project.
//
Make sure I have clear instructions on how to build and run your executables. If you're using C or C++, then provide a Makefile.

Submit via Blackboard. When you are ready to submit your program for grading, create a compressed archive of a directory containing only your project's source, and upload it to Blackboard. The directory's name should be the same as your net ID. If you need to include a note with your submission, put the note in a README file in the directory. Submit your project before 8:00 P.M. on the due date.