Can anyone here help me build a spam filter using naive bayes?

Build classifiers that classify text into spam or no-spam using naive bayes and at least one other technique.

I got to the part where I can input text and I'll get the output as spam/ham.

But my professor wasn't clear about what she wants:

• input: accept input training data (documents from each class: spam and non-spam)
• outputs: class assignment + confusion matrix + precision/recall, ROC curve or Precision/Recall curve while varying threshold parameters …, etc
• Uses machine learning classifiers: Try Naïve Bayes, and at least one other technique either using Weka or using python