Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.3/4434
Título: Probabilistic approach for comparing partitions
Autor: Silva, Osvaldo
Bacelar-Nicolau, Helena
Nicolau, Fernando C.
Sousa, Áurea
Palavras-chave: Hierarchical Cluster Analysis
Comparing Partitions
Affinity Coefficient
VL Methodology
Data: 2015
Editora: ISAST, International Society for the Advancement of Science and Technology
Citação: Silva, O.; Bacelar-Nicolau, H.; Nicolau, F. C.; & Sousa, Á. (2015). Probabilistic Approach for Comparing Partitions. In Raimondo Manca-Sally McClean-Christos H Skiadas (Eds), "New Trends in Stochastic Modeling and Data Analysis", (pp. 113-122). ISAST (International Society for the Advancement of Science and Technology).
Resumo: The comparison of two partitions in Cluster Analysis can be performed using various classical coefficients (or indexes) in the context of three approaches (based, respectively, on the count of pairs, on the pairing of the classes and on the variation of information). However, different indexes usually highlight different peculiarities of the partitions to compare. Moreover, these coefficients may have different variation ranges or they do not vary in the predicted interval, but rather only in one of their subintervals. Furthermore, there is a great diversity of validation techniques capable of assisting in the choice of the best partitioning of the elements to be classified, but in general each one tends to favour a certain kind of algorithm. Thus, it is useful to find ways to compare the results obtained using different approaches. In order to assist this assessment, a probabilistic approach to comparing partitions is presented and exemplified. This approach, based on the VL (Validity Linkage) Similarity, has the advantage, among others, of standardizing the measurement scales in a unique probabilistic scale. In this work, the partitions obtained from the agglomerative hierarchical cluster analysis of a dataset in the field of teaching are evaluated using classical and probabilistic (of VL type) indexes, and the obtained results are compared.
URI: http://hdl.handle.net/10400.3/4434
ISBN: 978-618-5180-06-5 (Print)
978-618-5180-10-2 (e-ISBN)
Aparece nas colecções:DME - Parte ou Capítulo de um Livro / Part of Book or Chapter of Book
CICS/A - Parte ou Capítulo de um Livro / Part of Book or Chapter of Book

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