GSIT Researchers awarded Best Paper

Associate Professor Kai Ming Ting and Masters student Mr Fei Tony Liu were awarded the Best Paper (and Best Student Paper) at the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006) in Singapore on 9-12 April.

Their paper titled ‘Variable Randomness in Decision Tree Ensembles’ reports recent work on decision tree ensembles that employ randomisation to generate multiple models, in particular decision trees that are generated using a complete-random process. This work is motivated to find out the reasons why complete-random tree ensembles work in practice. It begins with an investigation on the strengths and weaknesses of complete-random tree ensembles. That leads us to introduce a variable randomness that allows the ensembles to work well in different kinds of data. Experimental results show that the proposed ensemble approach is significantly better than existing approaches such as Random Forests and Max-diverse Ensemble, and it is comparable to the state-of-the-art C5 boosting.

Associate Professor Kai Ming Ting (right) is congratulated on his award.