Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-12568-8_51 | PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014 |
Keywords | Field | DocType |
Feature selection, Testor Theory, typical testor algorithms | Row,Feature selection,Computer science,Matrix (mathematics),Algorithm,Theoretical computer science,Artificial intelligence | Conference |
Volume | ISSN | Citations |
8827 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eduardo Alba-Cabrera | 1 | 45 | 5.00 |
| Julio Ibarra-Fiallo | 2 | 3 | 2.46 |
| Salvador Godoy-Calderón | 3 | 3 | 4.49 |
| Fernando Cervantes-Alonso | 4 | 0 | 0.34 |