Another move toward the minimum consistent subset: A tabu search approach to the condensed nearest neighbor rule

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 31, Issue 3, 2001, Pages 408-413

  Cerveron V ^a   Ferri, F J ^a  

^a UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Multiple prototype classifiers; Nearest neighbors; Prototype selection; Tabu search

Indexed keywords

COMPUTATIONAL COMPLEXITY; DATABASE SYSTEMS; GENETIC ALGORITHMS; HEURISTIC METHODS; OPTIMIZATION; SOFTWARE PROTOTYPING; VECTORS;

MULTIPLE-PROTOTYPE CLASSIFIERS;

PATTERN RECOGNITION;

EID: 0035359888     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/3477.931531     Document Type: Article

References (13)

1. Selection of the optimal prototype subset for 1-NN classification
2. Multiple prototype classifier design
3. Nearest prototype classification: Clustering, genetic algorithms, or random search
4. The condensed nearest neighbor rule
5. The reduced nearest neighbor role
6. Minimal consistent set (MCS) identification for optimal nearest neighbor decision systems design
7. The condensed nearest neighbor rule using the concept of mutual nearest neighborhood
8. Parallel random search and tabu search for the minimal consistent subset selection problem
9. A tabu search approach to the clustering problem
10. The use of multiple measurements in taxonomic problems