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A Hierarchical and Parallel Support Vector Machines Algorithm for Reducing the Training Time(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2005年01期
Page:
8-11
Research Field:
Publishing date:

Info

Title:
A Hierarchical and Parallel Support Vector Machines Algorithm for Reducing the Training Time
Author(s):
WEN Yimin;  LIAO Hongyuan;  ZHOU Lihua
Department of Information Engineering, Hunan Industry Polytechnic, Hunan Changsha 410007, China
Keywords:
h ie rarch ica l filtering;  support vectorm ach ines;  cross- comb in ing
PACS:
TP181
DOI:
-
Abstract:
Based on the essence of suppo rt vec to rs and pa ra lle l a lgor ithm, the paper proposes a nove l strategy of filtering the tra in ing sam ples in a hierarchica l and para llel w ay to speed up the tra ining o f support vector m ach ines ( SVM s). Dur ing the training pro cess, the entire c lassifica tion problem is d iv ided into several sm a ll sub- problem s that can be handled in a para llel w ay. H av ing h ie rarch ically filtered out the non- support-vec to r data, w e can obta in the final training data se t, wh ich is used to tra in a SVM tha t w ill be used as the final pattern c lassifie r. In order to keep the consistency, the cross- comb ining pr inciple is introduced. The simu la tion resu lts illustrate that ourm ethod speeds up tra in ing wh ilem a inta in ing the genera lization accuracy o f SVM s

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Last Update: 2013-04-29