Anzeige
Erschienen in:
2011 | OriginalPaper | Buchkapitel
Mining Coherent Biclusters with Fish School Search
verfasst von : Lara Menezes, André L. V. Coelho
Erschienen in: Advances in Swarm Intelligence
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Fish School Search (FSS) is a recently-proposed metaheuristic inspired by the collective behavior of fish schools. In this paper, we provide a preliminary assessment of FSS while coping with the task of mining coherent and sizeable biclusters from gene expression and collaborative filtering data. For this purpose, experiments were conducted on two real-world datasets whereby the performance of FSS was compared with that exhibited by two other population-based metaheuristics, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The results achieved demonstrate the usefulness of FSS while tackling the biclustering problem.