In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
We propose a new classification method for prediction of drug properties, called the Random Feature Subset Boosting for Linear Discriminant Analysis (LDA). The main novelty of this...
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...
Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...