|Table of Contents|

Design of L1 Norm Maximum Margin Classifier(PDF)

《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2018年04期
Page:
59-
Research Field:
·数学与计算机科学·
Publishing date:

Info

Title:
Design of L1 Norm Maximum Margin Classifier
Author(s):
Kou Zhenyu1Yang Xubing1Zhang Fuquan1Yang Hongxin1Xu Dengping2
(1.College of Information Science and Technology,Nanjing Forestry University,Nanjing 210037,China)(2.Survey & Planning Institute of State Forestry Administration,Beijing 100714,China)
Keywords:
L1 normsupport vector machinemarginlinear programming
PACS:
TP391
DOI:
10.3969/j.issn.1001-4616.2018.04.010
Abstract:
L1 norm is taken as an example to design an L1 norm L1MMC(L1-norm Maximum Margin Classifier). The main features are as follows:(1)The interval is represented by the point-to-plane distance analysis of the L1 norm;(2)This classifier,like SVM,maximizes the L1 interval to minimize the risk of both empirical and structural risks;(3)Only need to be solved through linear programming to avoid the quadratic programming problem of SVM;(4)Classification accuracy reaches or even exceeds SVM. Finally,on the artificial data and the international standard UCI data set,verify the effectiveness of the method.

References:

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Last Update: 2018-12-30