PT Unknown
AU Pierluigi Casale
   Oriol Pujol
   Petia Radeva
TI Approximate Convex Hulls Family for One-Class Cassification
BT 10th International Workshop on Multiple Classifier Systems
PY 2011
BP 106
EP 115
VL 6713
DI 10.1007/978-3-642-21557-5_13
AB In this work, a new method for one-class classification based on the Convex Hull geometric structure is proposed. The new method creates a family of convex hulls able to fit the geometrical shape of the training points. The increased computational cost due to the creation of the convex hull in multiple dimensions is circumvented using random projections. This provides an approximation of the original structure with multiple bi-dimensional views. In the projection planes, a mechanism for noisy points rejection has also been elaborated and evaluated. Results show that the approach performs considerably well with respect to the state the art in one-class classification.
ER