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 ...
In this work we introduce a new distance estimation technique by boosting and we apply it to the K-Nearest Neighbor Classifier (KNN). Instead of applying AdaBoost to a typical cla...
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
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...
Abstract. Bag-of-words representation with visual keypoints has recently emerged as an attractive approach for video search. In this paper, we study the degree of improvement when ...