Optimal selection of reference set for the nearest neighbor classification by Tabu search

2001 ◽  
Vol 16 (2) ◽  
pp. 126-136
Author(s):  
Hongbin Zhang ◽  
Guangyu Sun
2004 ◽  
Vol 33 (9) ◽  
pp. 2137-2157 ◽  
Author(s):  
David A. Johannsen ◽  
Edward J. Wegman ◽  
Jeffrey L. Solka ◽  
Carey E. Priebe

Author(s):  
Hisao Ishibuchi ◽  
◽  
Tomoharu Nakashima

This paper proposes a genetic-algorithm-based approach for finding a compact reference set in nearest neighbor classification. The reference set is designed by selecting a small number of reference patterns from a large number of training patterns using a genetic algorithm. The genetic algorithm also removes unnecessary features. The reference set in our nearest neighbor classification consists of selected patterns with selected features. A binary string is used for representing the inclusion (or exclusion) of each pattern and feature in the reference set. Our goal is to minimize the number of selected patterns, to minimize the number of selected features, and to maximize the classification performance of the reference set. Computer simulations on commonly used data sets examine the effectiveness of our approach.


2007 ◽  
Vol 19 (3) ◽  
pp. 470-479 ◽  
Author(s):  
Emilio Carrizosa ◽  
Belén Martín-Barragán ◽  
Frank Plastria ◽  
Dolores Romero Morales

Author(s):  
Lin Qiu ◽  
Yanpeng Qu ◽  
Changjing Shang ◽  
Longzhi Yang ◽  
Fei Chao ◽  
...  

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