YYC: A fast performance incremental algorithm for finding typical testors

Eduardo Alba-Cabrera, Julio Ibarra-Fiallo, Salvador Godoy-Calderon, Fernando Cervantes-Alonso

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

8 Scopus citations

Abstract

The last few years have seen an important increase in research publications dealing with external typical testor-finding algorithms, while internal ones have been almost forgotten or modified to behave as external on the basis of their alleged poor performance. In this research we present a new internal typical testor-finding algorithm called YYC that incrementally calculates typical testors for the currently analized set of basic matrix rows by searching for compatible sets. The experimentally measured performance of this algorithm stands out favorably in problems where other external algorithms show very low performance. Also, a comparative analysis of its efficiency is done against some external typical testor-finding algorithms published during the last few years.

Original languageEnglish
Title of host publicationProgress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings
EditorsEduardo Bayro-Corrochano, Edwin Hancock
PublisherSpringer Verlag
Pages416-423
Number of pages8
ISBN (Electronic)9783319125671
DOIs
StatePublished - 2014
Event19th Iberoamerican Congress on Pattern Recognition, CIARP 2014 - Puerto Vallarta, Mexico
Duration: 2 Nov 20145 Nov 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8827
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
Country/TerritoryMexico
CityPuerto Vallarta
Period2/11/145/11/14

Keywords

  • Feature selection
  • Testor theory
  • Typical testor algorithms

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