Abstract
In this paper we present a study of the overlapping clustering algorithms OKM, WOKM and OKMED, which are extensions to the overlapping case of the well known Kmeans algorithm proposed for building partitions. Different to other previously reported comparisons, in our study we compare these algorithms using the external evaluation metric FBcubed which takes into account the overlapping among clusters and we contrast our results against those obtained by F-measure, a metric that does not take into account the overlapping among clusters and that has been previously used in another reported comparison.
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Aroche-Villarruel, A.A., Carrasco-Ochoa, J.A., Martínez-Trinidad, J.F., Olvera-López, J.A., Pérez-Suárez, A. (2014). Study of Overlapping Clustering Algorithms Based on Kmeans through FBcubed Metric. In: Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Olvera-Lopez, J.A., Salas-Rodríguez, J., Suen, C.Y. (eds) Pattern Recognition. MCPR 2014. Lecture Notes in Computer Science, vol 8495. Springer, Cham. https://doi.org/10.1007/978-3-319-07491-7_12
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DOI: https://doi.org/10.1007/978-3-319-07491-7_12
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