A novel ensemble algorithm for tumor classification

Zhan Li Sun, Han Wang, Wai Shing Lau, Gerald Seet, Danwei Wang, Kin Man Lam

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

From the viewpoint of image processing, a spectral feature-based TLS (Tikhonov-regularized least-squares) ensemble algorithm is proposed for tumor classification using gene expression data. In the TLS model, a test sample is represented as a linear combination of atoms of an overcomplete dictionary. Two types of dictionaries, spectral feature-based eigenassays and spectral feature-based metasamples, are proposed for the TLS model. Experimental results on standard databases demonstrate the feasibility and effectiveness of the proposed method.
Original languageEnglish
Title of host publicationAdvances in Neural Networks, ISNN 2013 - 10th International Symposium on Neural Networks, Proceedings
Pages292-298
Number of pages7
EditionPART 2
DOIs
Publication statusPublished - 1 Aug 2013
Event10th International Symposium on Neural Networks, ISNN 2013 - Dalian, China
Duration: 4 Jul 20136 Jul 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7952 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Symposium on Neural Networks, ISNN 2013
Country/TerritoryChina
CityDalian
Period4/07/136/07/13

Keywords

  • gene expression data
  • Tikhonov- regularized least-squares model
  • Tumor classification

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this