A Convex Combination of Models for Predicting Road Traffic

This paper describes an approach to the road traffic prediction problem in Warsaw in the context of a data mining competition that is part of the IEEE ICDM 2010. A solution based on a convex combination of models mining different wells of information within the data is described. Such convex combination allows the final model compensate highly uncorrelated errors from the different underlying models and to achieve higher prediction accuracy.