Optimisation on support vector machines

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2000

Autores

Pedroso, JP (Autor) Outra; Murata, N (Autor) Outra

Ata de Conferência Internacional

Título: IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL VI

Páginas: 399-404

IEEE/INNS/ENNS International Joint Conference on Neural Networks (IJCNN 2000)

COMO, ITALY, JUL 24-27, 2000

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 2 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: P-001-1N3

DOI: 10.1109/IJCNN.2000.859428

Abstract (EN): In this paper we deal with the optimisation problem involved in determining the maximal margin separation hyperplane in support vector machines. We consider three different formulations, based on L-2 norm distance (the standard case), L-1 norm, and L-infinity norm. We consider separation in the original space of the data (i.e., there are no kernel transformations). For any of these cases, we focus on the following problem: having the optimal solution for a given training data set, one is given a new training example. The purpose is to use the information about the solution of the problem without the additional example in order to speed up the new optimisation problem. We also consider the case of reoptimisation after removing an example from the data set. We report results obtained for some standard benchmark problems.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6