A Research on Ensembles Method for One Class Classification Using Convex Hull Polytope Model

Classification is a data mining task that allocated similar data to categories or classes. One of the most general methods for classification is ensemble method which refers supervised learning. After generating classification rules we can apply those rules on unidentified data and achieve the results. In oneclass classification it is supposed that only information of one of the classes, the target class, is available. In an ensemble classification system, different base classifiers are combined in order to obtain a classifier with higher performance. In this work, a new one-class classification ensemble strategy called Approximate Polytope Ensemble is presented. The geometrical theory of convex hull is used to define the boundary of the target class defining the problem. Keywords— Bagging, Boosting, Classification, Ensembles, One Class Classification, convex hull, polytope