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2016 | OriginalPaper | Chapter

Hierarchy of Groups Evaluation Using Different F-Score Variants

Authors : Michał Spytkowski, Łukasz P. Olech, Halina Kwaśnicka

Published in: Intelligent Information and Database Systems

Publisher: Springer Berlin Heidelberg

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Abstract

The paper presents a cursory examination of clustering, focusing on a rarely explored field of hierarchy of clusters. Based on this, a short discussion of clustering quality measures is presented and the F-score measure is examined more deeply. As there are no attempts to assess the quality for hierarchies of clusters, three variants of the F-Score based index are presented: classic, hierarchical and partial order. The partial order index is the authors’ approach to the subject. Conducted experiments show the properties of the considered measures. In conclusions, the strong and weak sides of each variant are presented.

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Andreopoulos, B., An, A., Wang, X., Schroeder, M.: A roadmap of clustering algorithms: finding a match for a biomedical application. Brief. Bioinform. 10(3), 297–314 (2009)CrossRef

Blundell, C., Teh, Y.W., Heller, K.A.: Bayesian rose trees. arXiv preprint. (2012). arxiv:1203.3468

Cimiano, P., Hotho, A., Staab, S.: Comparing conceptual, divise and agglomerative clustering for learning taxonomies from text. In: de Mántaras, R.L., Saitta, L. (eds.) Proceedings of the 16th Eureopean Conference on AI, Spain, pp. 435–439. IOS Press (2004)

Desgraupes, B.: Clustering indices (2013). https://cran.r-project.org/web/packages/clusterCrit/vignettes/clusterCrit.pdf

Everitt, B.S., Landau, S., Leese, M., Stahl, D.: Cluster Analysis. John Wiley and Sons Ltd, New York (2011)CrossRefMATH

Ghahramani, Z., Jordan, M.I., Adams, R.P.: Tree-structured stick breaking for hierarchical data. In: NIPS, pp. 19–27 (2010)

Hartigan, J.A., Wong, M.A.: Algorithm as 136: A k-means clustering algorithm. Appl. Stat. 28(1), 100–108 (1979)CrossRefMATH

Jain, A.K.: Data clustering: 50 years beyond k-means. Pattern Recogn. Lett. 31(8), 651–666 (2010)CrossRef

Kogan, J., Nicholas, C.K., Teboulle, M.: Grouping Multidimensional Data: Recent Advances in Clustering. Springer, Heidelberg (2006)CrossRefMATH

10.

Larsen, B., Aone, C.: Fast and effective text mining using linear-time document clustering. In: Fayyad, U.M., Chaudhuri, S., Madigan, D. (eds.) Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, USA, pp. 16–22. ACM (1999)

11.

Madhulatha, T.S.: An overview on clustering methods. CoRR abs/1205.1117 (2012)

12.

Mirzaei, A., Rahmati, M., Ahmadi, M.: A new method for hierarchical clustering combination. Intell. Data Anal. 12(6), 549–571 (2008)

13.

Oded, M., Lior, R. (eds.): Data Mining and Knowledge Discovery Handbook. Springer, New York (2010)MATH

14.

Olech, L.P., Paradowski, M.: Hierarchical gaussian mixture model with objects attached to terminal and non-terminal dendrogram nodes. In: 9th International Conference on Computer Recognition Systems, Poland (2015)

15.

Pohl, D., Bouchachia, A., Hellwagner, H.: Social media for crisis management: clustering approaches for sub-event detection. Multimed. Tools Appl. 74(11), 3901–3932 (2015)CrossRef

16.

van Rijsbergen, C.J.: Information Retrieval. Butterworth, London (1979)MATH

17.

Sevillano, X., Valero, X., Alas, F.: Look, listen and find: A purely audiovisual approach to online videos geotagging. Inf. Sci. 295, 558–572 (2015)CrossRef

18.

Spytkowski, M., Kwasnicka, H.: Hierarchical clustering through bayesian inference. In: Nguyen, N.-T., Hoang, K., Jȩdrzejowicz, P. (eds.) ICCCI 2012, Part I. LNCS, vol. 7653, pp. 515–524. Springer, Heidelberg (2012)

19.

Xu, R., Wunsch, D.: Survey of clustering algorithms. Trans. Neur. Netw. 16(3), 645–678 (2005)CrossRef

Title: Hierarchy of Groups Evaluation Using Different F-Score Variants
Authors: Michał Spytkowski
Łukasz P. Olech
Halina Kwaśnicka
Publisher: Springer Berlin Heidelberg
Book: Intelligent Information and Database Systems
Print ISBN: 978-3-662-49380-9

Electronic ISBN: 978-3-662-49381-6

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-3-662-49381-6_63

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