Project 1: Spam Filter


Type of Project: Implementation


Study various spam filtering techniques based on machine learning.

Summarize the various methods.

Implement one of them

Test the method.

Try to make a prototype and integrate with a standard mailing system


Some references:

1)      Bayesian Spam filtering

2)      Graham, Paul (2002). A Plan for Spam.

3)      Here you will find some spam filter product reviews

4)      Some papers: (a) Johan Hovoltd

                                  (b) Androutsopoulos et al.

                                  (c) Androutsopoulos et al



Project 2: Face Recognition


Type of project: Experiment / Implementation


Implement a face recognition algorithm and test it on a standard data set.



Some references:

1) The face recognition page



Project 3: Ensemble Methods


Type of project: Theory/Methodology


Study the various ensemble methods available in literature

Propose a new ensemble technique, may be specific to a classifier.



Some references:

1)      Bagging

2)      Boosting

3)      Kuncheva and Whitaker

4)      Rodríguez, Kuncheva and  Alonso



Project 4: Graph Clustering


Study some graph clustering algorithms and implement one of them.


Some references

1 http:/







Project 5: SVM Regression


Implement the SMO algorithm for Support Vector regression.






Project 6: K-NN Variants


Study implement and compare some K-NN variants.