@inproceedings{214cb00fec7842ab82d28e7fda3f2cb4,
title = "An improved projection pursuit clustering model and its application based on Quantum-behaved PSO",
abstract = "Extracting the information with biological significance from gene expression data is an important research direction. Clustering algorithms in this area have been increasingly widely applied. According to the characteristic of gene expression data, the improved projection pursuit cluster model was introduced in this area and Quantum-behaved Particle Swarm Optimization(QPSO) was put forward to find the optimal projection direction. The simulation results showed that the improved strategy was feasible and effective. This method is not only a new way for the massive high-dimensional data clustering, but also provides a new approach for the cluster analysis of gene expression data.",
keywords = "Clustering, Gene expression data, Projection pursuit, QPSO",
author = "Qun Zhang and Xiujuan Lei and Xu Huang and Aidong Zhang",
year = "2010",
doi = "10.1109/ICNC.2010.5583182",
language = "English",
isbn = "9781424459612",
series = "Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010",
publisher = "IEEE Computer Society",
pages = "2581--2585",
booktitle = "Proceedings - 2010 6th International Conference on Natural Computation, ICNC 2010",
address = "United States",
}