Abstract. Assume we are given a sample of points from some underlying distribution which contains several distinct clusters. Our goal is to construct a neighborhood graph on the sa...
Class binarizations are effective methods for improving weak learners by decomposing multi-class problems into several two-class problems. This paper analyzes how these methods can...
Haiku is a data mining system which combines the best properties of human and machine discovery. An self organising visualisation system is coupled with a genetic algorithm to prov...
Attribute subsetting is a meta-classification technique, based on learning multiple base-level classifiers on projections of the training data. In prior work with nearest-neighbour...
Michael Horton, R. Mike Cameron-Jones, Raymond Wil...
Nearest neighbor forecasting models are attractive with their simplicity and the ability to predict complex nonlinear behavior. They rely on the assumption that observations simila...