Finding Groups in Data: Cluster Analysis with Ants

We present in this paper a modification of Lumer and Faieta’s algorithm for data clustering. This algorithm discovers automatically clusters in numerical data without prior knowledge of possible number of clusters. We have applied this algorithm on standard databases and we get very good results compared to the AntClass, k–means and ISODATA algorithms for IRIS dataset.

• Type: Conference
• Year: 2006
• Where: ISDA
• Authors: Urszula Boryczka
• Keywords: Algorithms, Data Clustering, ISDA 2006, Numerical Data, Operating Systems