Nmap Development mailing list archives
Prabhjyot's Status Report: #9 of 17
From: Prabhjyot Singh Sodhi <prabhjyotsingh95 () gmail com>
Date: Tue, 28 Jun 2016 10:33:28 +0530
Hey list, This week went by quick, but I think I'm finally closing upon the random forest experimentation. So, here's what all was done, Accomplishments: - As reported last week I have been trying to convert the opencv implementation to return the top 3 predictions instead of just one. This basically involves getting votes from individual trees of the random forest. I have tried to post questions to the opencv forum and their IRC channel but haven't had success yet. - For testing the new db, I tried two methods. (As of now both use accuracy measure) 1) Stratified sampling: I formed a 80:20 class wise split for each class, where 80 % prints are used for training and 20% used for testing. This method yielded a total of 68 prints in the testing set. The Liblinear model was able to 40 prints correctly (64.4%) while the random forest was able to predict 52 prints correctly (81%) 2) Randomized testing: In this case I selected a set of either 20 or 40 prints randomly (instead of class wise). I repeated this test for around 15 times and the random forest model performed better each time (in terms of accuracy) (I will update nmap-private-dev to contain these test results) - This week I also worked on documenting the changes made to the db, the model that is being used. I hope to push it to nmap-private-dev in a week's time for feedback. - Lastly I passed GSoC's Midterm evaluation, yay!. I'd also like to congratulate other participants who passed Priorities: - Work on documentation - experiment with using specificity and sensitivity (or precision and recall) in addition to accuracy while testing models. - Start working on the multi-stage classifier Cheers, Prabhjyot
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- Prabhjyot's Status Report: #9 of 17 Prabhjyot Singh Sodhi (Jun 27)