A new approach of data clustering using a flock of agents.
This paper presents a new bio-inspired algorithm (FClust) that dynamically creates and visualizes groups of data. This algorithm uses the concepts of a flock of agents that move together in a complex manner with simple local rules. Each agent represents one data. The agents move together in a 2D environment with the aim of creating homogeneous groups of data. These groups are visualized in real time, and help the domain expert to understand the underlying structure of the data set, like for example a realistic number of classes, clusters of similar data, isolated data. We also present several extensions of this algorithm, which reduce its computational cost, and make use of a 3D display. This algorithm is then tested on artificial and real-world data, and a heuristic algorithm is used to evaluate the relevance of the obtained partitioning.
Picarougne
Fabien
F
Laboratoire d'Informatique Nantes Atlantique, Ecole Polytechniques de l'Université de Nantes, Département Informatique, La Chantrerie, rue Christian Pauc BP 50609 44306 Nantes Cedex 3, France. fabien.picarougne@univ-nantes.fr
Azzag
Hanene
H
Venturini
Gilles
G
Guinot
Christiane
C
D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D019295:Computational Biology; D003627:Data Interpretation, Statistical; D019992:Databases as Topic; D006801:Humans; D008954:Models, Biological; D008957:Models, Genetic; D015233:Models, Statistical; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D012867:Skin / Q000378:metabolism; D013025:Glycine max / Q000378:metabolism