| DOI | Resolve DOI: https://doi.org/10.1007/978-3-319-25210-0_19 |
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| Author | Search for: LaPlante, François; Search for: Belacel, Nabil1; Search for: Kardouchi, Mustapha |
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| Affiliation | - National Research Council of Canada. Information and Communication Technologies
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| Format | Text, Book Chapter |
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| Conference | 6th International Conference, ICAART 2014, March 6-8, 2014, Angers, France |
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| Subject | data mining; automatic clustering; unsupervised learning |
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| Abstract | We 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. |
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| Publication date | 2015 |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 23000657 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 4bc10ce2-e257-4526-b42f-74ed8e6a3002 |
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| Record created | 2016-08-18 |
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| Record modified | 2020-06-11 |
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