A DIAMOND method for classifying biological data

Han-Lin Li*, Yao Huei Huang, Ming Hsien Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


This study proposes an effective method called DIAMOND to classify biological and medical data. Given a set of objects with some classes, DIAMOND separates the objects into different cubes, where each cube is assigned to a class. Via the union of these cubes, we utilize mixed integer programs to induce classification rules with better rates of accuracy, support and compactness. Two practical data sets, one of HSV patient results and the other of Iris flower, are tested to illustrate the advantages of DIAMOND over some current methods.

Original languageEnglish
Title of host publicationMedical Biometrics - Second International Conference, ICMB 2010, Proceedings
Number of pages11
StatePublished - 21 Jul 2010
Event2nd International Conference on Medical Biometrics, ICMB 2010 - Hong Kong, China
Duration: 28 Jun 201030 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6165 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Conference on Medical Biometrics, ICMB 2010
CityHong Kong


  • Classification rules
  • Integer Program

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