Voting with a parameterized veto strategy
Domonkos Tikk, Zsolt T. Kardkovács, Ferenc Szidarovszky · ACM SIGKDD Explorations Newsletter · 2006
This paper presents our winner solution for the KDD Cup 2006 problem. It is based on the results of three different supervised learning techniques which are then combined in a classifier committee, and finally a single solution is obtained with a voting procedure. The voting procedure assigns weights to each member of the committee according to their average performance on a ten-fold cross-validation test and it also takes into account the confidence values returned by the three algorithms. The final decision of the committee is determined by means of a parameterized veto strategy, which takes into consideration the maximal allowed error rate beside the confidence values of the committee members. The solution presented here won Task 2 and became runner-up at Task 1 in the competition.