RESEARCH ON GREEDY CLIQUE PARTITION-GCP ALGORITHM
Clustering of binary fingerprints is used in the classification of gene expression data. It is known that the clustering of binary fingerprints with 3 bits of missing value is NP-Hard. The Greedy Clique Partition (GCP for short) algorithm is a heuristic algorithm used to clustering of binary fingerprints with missing values. In this paper, we firstly study the feature of instances which can not be resolved by the GCP based on hash table. Then a new property of problem instances is given, which can further improve the heuristic algorithm based on linked list. Finally, an empirical formula is presented, which is used to judge the accuracy and credibility of the GCP algorithm.
Clustering gene expression data algorithm clique partition
PEI-QIANG LIU
School of Information & Electronic Engineering, Shandong Institute of Business and Technology, Yantai 264005, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
4306-4309
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）