A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering.

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Title: A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering.
Authors: Randel, Rodrigo1, rodrigo.randel@polymtl.ca, Aloise, Daniel1, Blanchard, Simon J.2, Hertz, Alain3
Source: Data Mining & Knowledge Discovery; Nov2021, Vol. 35 Issue 6, p2341-2368, 28p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 153318687
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=153318687
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      – Type: doi
        Value: 10.1007/s10618-021-00794-0
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      – Code: eng
        Text: English
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        PageCount: 28
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      – TitleFull: A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering.
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            NameFull: Randel, Rodrigo
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            NameFull: Aloise, Daniel
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            NameFull: Blanchard, Simon J.
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              Text: Nov2021
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              Y: 2021
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              Value: 35
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