Using ROC Curves

As a homework of machine learning course, I'm implementing a spam filter with Naive Bayes classifier. To evaluate the performance, I wanted to use ROC curve, but I was unsure of how can I use it in a proper way. So I found the following tutorial extremely useful:

http://www.cs.bris.ac.uk/~flach/ICML04tutorial/

It has a lot of materials, maybe a little too much since I'm not that committed to the theory of ROC curve for now, but maybe I should definitely return to this material since this is surely of practical importance.

My labmate Nguyen Cao informed me about the R package on ROC curves. I haven't taken a serious look at it yet, but it looks pretty nice. Following is the link to the website:

http://rocr.bioinf.mpi-sb.mpg.de/

There are a lot of things to learn...! :D

Installed doxygen + doxymacs

I'm trying to learn to use Doxygen.

http://www.stack.nl/~dimitri/doxygen/

This way I hope I can learn to document my code better :)

The following page helped me install doxymacs, emacs plug-in for doxygen.
(Actually what I had to do was just to type apt-get install doxymacs)
http://emacs-fu.blogspot.com/2009/01/commenting-your-functions.html


Then I confronted the problem of not displaying my e-mail address correctly.
I think this is because I didn't configure my Ubuntu properly, but at least I could find that

 (setq user-mail-address "my@email.com")

will set my user-mail-address variable, and would propagate to doxymacs-user-mail-address.

As a statistics Ph.D student, I felt obliged to know how to document R codes (although R is not my favorite language for scientific computation). The solution is to try Roxygen in the following project page:

http://roxygen.org/

It's good that ESS (Emacs Speaks Statistics) supports Roxygen! Actually I've never done anything ambitious in R (just homework problems), but I would definitely try to use Roxygen when the appropriate time comes!