We propose an omnivariate decision tree architecture which contains univariate, multivariate linear or nonlinear nodes, matching the complexity of the node to the complexity of the...
Most data mining algorithms and tools stop at discovered customer models, producing distribution information on customer profiles. Such techniques, when applied to industrial pro...
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...
A decision tree induction method for multilabel classification tasks (IS-MLT) is presented which uses an iterative approach for determining the best split at each node. The propo...
Abstract. Ensemble methods are able to improve the predictive performance of many base classifiers. Up till now, they have been applied to classifiers that predict a single target ...
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzerosk...