Abstract : In order to solve the local convergence problem of the Cross Entropy Clustering algorithm, a split-and-merge operation is introduced to escape from local minima and reach a better solution. We describe the theoretical aspects of the method in a limited space, present a few strategies of tweaking the clustering algorithm and compare them with existing solutions. The experiments show that the presented approach increases flexibility and effectiveness of the whole algorithm.
Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.193-204, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_17〉
https://hal.inria.fr/hal-01656257
Contributeur : Hal Ifip
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Soumis le : mardi 5 décembre 2017 - 14:59:27
Dernière modification le : mercredi 6 décembre 2017 - 01:20:58
Krzysztof Hajto, Konrad Kamieniecki, Krzysztof Misztal, Przemysław Spurek. Split-and-merge Tweak in Cross Entropy Clustering. Khalid Saeed; Władysław Homenda; Rituparna Chaki. 16th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Jun 2017, Bialystok, Poland. Springer International Publishing, Lecture Notes in Computer Science, LNCS-10244, pp.193-204, 2017, Computer Information Systems and Industrial Management. 〈10.1007/978-3-319-59105-6_17〉. 〈hal-01656257〉
