We present an online adaptive clustering algorithm in a decision tree framework which has an adaptive tree and a code formation layer. The code formation layer stores the represen...
A new algorithm for building decision tree classifiers is proposed. The algorithm is executed in a distributed environment and is especially designed for classifying large datase...
Mostexisting decision tree systemsuse a greedyapproachto inducetrees -- locally optimalsplits are inducedat every node of the tree. Althoughthe greedy approachis suboptimal,it is ...
Skyline computation is widely used in multi-criteria decision making. As research in uncertain databases draws increasing attention, skyline queries with uncertain data have also ...
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...