A Clustering Algorithm for Data Mining Based on Swarm Intelligence

Autor: Peng Jin, Yunlong Zhu, Kun-Yuan Hu
Rok vydání: 2007
Předmět:
Zdroj: 2007 International Conference on Machine Learning and Cybernetics.
DOI: 10.1109/icmlc.2007.4370252
Popis: Clustering analysis is an important function of data mining. Various clustering methods are need for different domains and applications. A clustering algorithm for data mining based on swarm intelligence called Ant-Cluster is proposed in this paper. Ant-Cluster algorithm introduces the concept of multi-population of ants with different speed, and adopts fixed moving times method to deal with outliers and locked ant problem. Finally, we experiment on a telecom company's customer data set with SWARM, agent-based model simulation software, which is integrated in SIMiner, a data mining software system developed by our own studies based on swarm intelligence. The results illuminate that Ant-Cluster algorithm can get clustering results effectively without giving the number of clusters and have better performance than k-means algorithm.
Databáze: OpenAIRE