Research on an improved algorithm for cluster analysis

摘要

Cluster analysis is an important data mining technique used to find data segmentation and pattern information. By clustering the data, people can obtain the data distribution, observe the character of each cluster, and make further study on particular clusters. In addition, cluster analysis usually acts as the preprocessing of other data mining operations. Therefore, cluster analysis has become a very active research topic in data mining. By improving the algorithm of classical Q-mode factor model, we put forward a new clustering method for large-scaled database: Q-Mode Factor Clustering Method, which dramatically reduce the time complexity of the algorithm.