A heuristic automatic clustering method based on hierarchical clustering

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DOIResolve DOI: http://doi.org/10.1007/978-3-319-25210-0_19
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TypeBook Chapter
Proceedings titleAgents and Artificial Intelligence: 6th International Conference, ICAART 2014, Angers, France, March 6-8, 2014, Revised Selected Papers
Series titleLecture Notes in Computer Science; Volume 8946
Conference6th International Conference, ICAART 2014, March 6-8, 2014, Angers, France
ISSN0302-9743
1611-3349
ISBN978-3-319-25209-4
978-3-319-25210-0
Pages312328
SubjectData-mining; Automatic clustering; Unsupervised learning
AbstractWe propose a clustering method which produces valid results while automatically determining an optimal number of clusters. The proposed method achieves these results with minimal user input, of which none pertains to a number of clusters. Our method’s effectiveness in clustering, including its ability to produce valid results on data sets presenting nested or interlocking shapes, is demonstrated and compared with cluster validity analysis to other methods to which a known optimal number of clusters is provided, and to other automatic clustering methods. Depending on the particularities of the data set used, our method has produced results which are roughly equivalent or better than those of the compared methods.
Publication date
LanguageEnglish
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number23000657
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Record identifier4bc10ce2-e257-4526-b42f-74ed8e6a3002
Record created2016-08-18
Record modified2016-08-18
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