ConferencePaper
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  (2009)

L2-SVM training with distributed data

Lodi, S; Sartori, C; Ñanculef R.

Keywords: model, support, parameters, machines, training, agent, example, data, distributed, vector, source, svm, based, User-defined, One-pass

Abstract

We propose an algorithm for the problem of training a SVM model when the set of training examples is horizontally distributed across several data sources. The algorithm requires only one pass through each remote source of training examples, and its accuracy and efficiency follow a clear pattern as function of a user-defined parameter. We outline an agent-based implementation of the algorithm. © 2009 Springer Berlin Heidelberg.

Más información

Título de la Revista: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen: 5774
Editorial: Society of Laparoendoscopic Surgeons
Fecha de publicación: 2009
Página de inicio: 208
Página final: 213
URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-70350405150&partnerID=q2rCbXpz