Implementation of Naive Bayes Classifier

NOTE All codes are based on MachineLearnigAction

This project consist of following functions

• Iporting a list of string from the exsiting documents
• Parse text into token vectors
• Train the bayes-classifier with these token vectors
• Use this classifier to determing if one e-mail is a spam e-mail

Steps for classifying spam email with naive Bayes

Example: using naïve Bayes to classify email

1. Collect: Text files provided.

2. Prepare: Parse text into token vectors.

3. Analyze: Inspect the tokens to make sure parsing was done correctly.

4. Train: Use trainNB0() that we created earlier.

5. Test: Use classifyNB() and create a new testing function to calculate the error rate over a set of documents.

6. Use: Build a complete program that will classify a group of documents and print misclassified documents to the screen.