Data Science and Classification | Zendy

Marie Chavent | Zendy; Yves Lechevallier | Zendy

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Data Science and Classification

Author(s) -

Marie Chavent,

Yves Lechevallier

Publication year - 2006

Publication title -

studies in classification, data analysis, and knowledge organization

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.145

H-Index - 21

eISSN - 2198-3321

pISSN - 1431-8814

DOI - 10.1007/3-540-34416-0

Subject(s) - cluster analysis , data mining , fuzzy clustering , computer science , artificial intelligence , hierarchical clustering , mathematics , pattern recognition (psychology)

DIVCLUS-T is a descendant hierarchical clustering methods based on the same monothetic approach than segmentation but from an unsupervised point of view. The dendrogram of the hierarchy is easy to interpret and can be read as decision tree. We present DIVCLUS-T on a small numerical and a small categorical example. DIVCLUS-T is then compared with two polythetic clustering methods: the Ward ascendant hierarchical clustering method and the k-means partitional method. The three algoritms are applied and compared on six databases of the UCI Machine Learning repository

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