Title :
A multiclass classification method by distance mapping learning network
Author :
Suzuki, Kenji ; Hashimoto, Shuji
Author_Institution :
Dept. of Appl. Phys., Waseda Univ., Tokyo, Japan
Abstract :
We propose a method of multiclass classification by utilizing a distance mapping learning network that is a distance-based multilayer perceptron The network can obtain the non-linear mapping between the input objects and the outputs by providing a pair of objects and the desired distance between them. It thus realizes multiclass classification based on pairwise classifications iteratively. We show the validity of the model with two classification problems: Iris classification and facial expression classification.
Keywords :
learning (artificial intelligence); multilayer perceptrons; pattern classification; Iris classification; distance mapping learning network; distance-based multilayer perceptron; facial expression classification; multiclass classification method; nonlinear mapping; Equations; Euclidean distance; Image databases; Iris; Learning systems; Multilayer perceptrons; Physics; Support vector machine classification; Support vector machines; World Wide Web;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1202200
