EvolveCluster: an evolutionary clustering algorithm for streaming data

Abstract Data has become an integral part of our society in the past years, arriving faster and larger quantities than before. Traditional clustering algorithms rely on availability entire datasets to model them correctly efficiently. Such requirements are not possible data stream scenario, where arrives needs be analyzed continuously. This paper proposes a novel evolutionary algorithm, entitled EvolveCluster, capable modeling evolving streams. We compare EvolveCluster against two other algorithms, PivotBiCluster Split-Merge Evolutionary Clustering, by conducting experiments three different datasets. Furthermore, we perform additional further evaluate its capabilities Our results show that manages capture behaviors adapts accordingly.