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Assessing variable importance in clustering: a new method based on unsupervised binary decision trees - MaRDI portal

Assessing variable importance in clustering: a new method based on unsupervised binary decision trees (Q1729346)

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scientific article; zbMATH DE number 7030233
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English
Assessing variable importance in clustering: a new method based on unsupervised binary decision trees
scientific article; zbMATH DE number 7030233

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    Assessing variable importance in clustering: a new method based on unsupervised binary decision trees (English)
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    27 February 2019
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    unsupervised learning
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    CUBT
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    deviance
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    variable importance
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    variables ranking
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