1. Learning to Classify Documents Edwin Zhang Computer Systems Lab 2009-2010

2. Abstract Classifying documents
Will use a Bayesian method and calculate conditional probability
Use a set of Training Documents
Choose a set of features

3. Introduction Learning to Classify Documents Use a Bayesian Method
Code in Java

4. Background Naïve Bayes Classifier/Bayesian Method
computes the conditional probability p(T|D) for a given document D for every topic
Assigns the document D to the topic with the largest conditional probability

5. Development Program has two steps: Learning Prediction
training documents
conditional probability
features selection

6. Development Prediction
Predicting what a unknown document is talking about based on prediction section

7. Development (continued)
Created Document, Category classes
Document class deals with the documents, has two functions
Category class deals with the categories, has three classes
Each category contains an array of documents
Each document contains an array of terms.
Right now, my program:
Reads in documents
Creates array of categories, which has array of documents
Has two categories right now

8. Development (continued)
What I still need to do:
Get documents to read in so that my program can learn
Develop and program a learning formula
Test my program's learning
Add more categories

9. Expected Results
Initially, the program may have trouble classifying documents into the correct category
As the program learns more and improves its formulas, it will get better at classifying documents into the correct categories.

10. Works Cited http://www.nltk.org/book My dad
Chai, Kian Ming Adam, Hai Leong Chieu, and Hwee Tou Ng. ACM Poral. Assocation of Computing Machinery, Web. 14 Jan < &coll=Portal&dl=ACM&CFID= &CFTOKEN= >.

11. Works Cited (continued)
Eyheramendy, Susana, and David Madigan. "A Flexible Bayesian Generalized Linear Model for Dichotomous Response Data with an Application to Text Categorization." Lecture Notes-Monograph Series 54 (2007): JSTOR. Web. 25 Oct <
Lavine, Michael, and Mike West. "A Bayesian Method for Classification and Discrimination." Canadian Journal of Statistics 20.4 (1992): JSTOR. Web. 14 Jan <