scholarly journals Differentially Aberrant Region Detection in Array CGH Data Based on Nearest Neighbor Classification Performance

2010 ◽  
Vol 3 (0) ◽  
pp. 70-81
Author(s):  
Yuta Ishikawa ◽  
Ichiro Takeuchi
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.


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

2004 ◽  
Vol 33 (9) ◽  
pp. 2137-2157 ◽  
Author(s):  
David A. Johannsen ◽  
Edward J. Wegman ◽  
Jeffrey L. Solka ◽  
Carey E. Priebe

Sign in / Sign up

Export Citation Format

Share Document