Classification of chromosome sequences with entropy kernel and LKPLS algorithm

Zhenqiu Liu, Dechang Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Kernel methods such as support vector machines have been used extensively for various classification tasks. In this paper, we describe an entropy based string kernel and a novel logistic kernel partial least square algorithm for classification of sequential data. Our experiments with a human chromosome dataset show that the new kernel can be computed efficiently and the algorithm leads to a high accuracy especially for the unbalanced training data.

Original languageEnglish (US)
Title of host publicationAdvances in Intelligent Computing - International Conference on Intelligent Computing, ICIC 2005, Proceedings
EditorsDe-Shuang Huang, Xiao-Ping Zhang, Guang-Bin Huang
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783540282266
StatePublished - 2005
EventInternational Conference on Intelligent Computing, ICIC 2005 - Hefei, China
Duration: Aug 23 2005Aug 26 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3644 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherInternational Conference on Intelligent Computing, ICIC 2005

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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