Online boosting methods have recently been used successfully for tracking, background subtraction etc. Conventional online boosting algorithms emphasize on interchanging new weak ...
Boosting methods are known not to usually overfit training data even as the size of the generated classifiers becomes large. Schapire et al. attempted to explain this phenomenon i...
Boosted PRIM (Patient Rule Induction Method) is a new algorithm developed for two-class classification problems. PRIM is a variation of those Tree-Based methods ( [4] Ch9.3), seek...
Pei Wang, Young Kim, Jonathan R. Pollack, Robert T...
In this paper we present an improvement of the precision of classification algorithm results. Two various approaches are known: bagging and boosting. This paper describes a set of ...
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...