Auto Spam Filter Sort Program

AUTOMATIC SPAM FILTERING CSCE 2050 Term Project Due date: 12/09/2007 11:59PM Introduction In this project, you will be implementing an automatic spam filter. Some of the most successful spam filters rely on techniques for machine learning, which automatically learn the characteristics of spam from input training data. You will have to implement a Naïve Bayes spam filter, which is a simple yet powerful method for spam classification. Your task Your task is to implement the Naïve Bayes spam filter by using data structures of your choice. You are provided with a set of 110 training documents (55 spam, 55 non-spam), and 80 test documents. You will have to train the Naïve Bayes classifier on the 110 training documents, and then automatically annotate the documents in the test data. The correct classification of the test documents is also provided so that you can compare the quality of your automatic classification with the correct classification. You have the freedom to select the data structures and algorithms that you consider to be more efficient for this task. Of course, you will have to justify your decisions. What to turn in There are two main parts in this project, both of them contributing to the final project grade. [login to view URL] if possible include notes of the following roughly enough so I can write 1 -2 page project report that includes: - design issues, what are the problems you encountered and how you solved them - data structures you use, the decision behind selecting them - theoretical analysis of the running time of your algorithm - scalability issues: would your implementation be efficient in the case of very large training data sets (e.g., one million training items, as opposed to 100) - accuracy of your implementation: how well does your spam filter work on the test data & other remarks. ## Deliverables 1) Complete and fully-functional working program(s) in executable form as well as complete source code of all work [login to view URL] you can provide with a document, and obtain the classification of the document as spam/nonspam. Please include a README file with running instructions. 2) Deliverables must be in ready-to-run condition, as follows (depending on the nature of the deliverables): a) For web sites or other server-side deliverables intended to only ever exist in one place in the Buyer's environment--Deliverables must be installed by the Seller in ready-to-run condition in the Buyer's environment. b) For all others including desktop software or software the buyer intends to distribute: A software installation package that will install the software in ready-to-run condition on the platform(s) specified in this bid request. 3) All deliverables will be considered "work made for hire" under U.S. Copyright law. Buyer will receive exclusive and complete copyrights to all work purchased. (No GPL, GNU, 3rd party components, etc. unless all copyright ramifications are explained AND AGREED TO by the buyer on the site per the coder's Seller Legal Agreement). ## Platform Windows XP, MS-DOS