An improved projection pursuit clustering model and its application based on Quantum-behaved PSO

摘要

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.