Pattern clustering with statistical methods using a DNA-based algorithm.
Clustering is commonly exploited in engineering, management, and science fields with the objective of revealing structure in pattern data sets. In this article, through clustering we construct meaningful collections of information granules (clusters). Although the underlying goal is obvious, its realization is fully challenging. Given their nature, clustering is a well-known NP-complete problem. The existing algorithms commonly produce some suboptimal solutions. As a vehicle of pattern clustering, we discuss in this article how to use a DNA-based algorithm. We also discuss the details of encoding being used here with statistical methods combined with the DNA-based algorithm for pattern clustering.
Graduate School of Information, Production and Systems, Waseda University, Kitakyushu 808-0135, Japan. octoberkim@akane.waseda.jp
Ikno
I
Kim
Junzo
J
Watada
Witold
W
Pedrycz
Jui-Yu
JY
Wu
D000465:Algorithms; D001483:Base Sequence; D016000:Cluster Analysis; D003198:Computer Simulation; D004247:DNA / Q000737:chemistry*; D008957:Models, Genetic; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated / Q000379:methods*
D004247:DNA