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Abstract
Abstract. This article handles the problem of validating the results of nested (as opposed to "flat") clusterings. It shows that standard external validation indices used for partitioning clustering validation, like Rand statistics, Hubert Γ statistic or F-measure are not applicable in nested clustering cases. Additionally to the work, where F-measure was adopted to hierarchical classification as hF-measure, here some methods to get desired hRand and hΓ indices for nested clustering are presented. Introduced measures are evaluated and, as an exemplary application, a validation of nested clustering methods for Wikipedia articles using OPTICS algorithm is shown.
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Keywords
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- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Title of issue:
- Emerging Intelligent Technologies in Industry strony 208 - 225
- Language:
- English
- Publication year:
- 2011
- Bibliographic description:
- Draszawka K., Szymański J.: External Validation Measures for Nested Clustering of Text Documents// Emerging Intelligent Technologies in Industry/ ed. eds. Dominik Ryżko, Henryk Rybiński, Piotr Gawrysiak, Marzenia Kryszkiewicz : Springer, 2011, s.208-225
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-642-22732-5_18
- Verified by:
- Gdańsk University of Technology
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