Title :
Finding Groups in Data: Cluster Analysis with Ants
Author :
Boryczka, Urszula
Author_Institution :
Inst. of Comput. Sci., Silesia Univ., Sosnowiec
Abstract :
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
Keywords :
artificial life; optimisation; pattern clustering; ant-based clustering; data clustering; Algorithm design and analysis; Clustering algorithms; Computer science; Data analysis; Data mining; Databases; Iris; Partitioning algorithms; Simulated annealing; Sorting;
Conference_Titel :
Intelligent Systems Design and Applications, 2006. ISDA '06. Sixth International Conference on
Conference_Location :
Jinan
Print_ISBN :
0-7695-2528-8
DOI :
10.1109/ISDA.2006.151
