Limitations of Clustering with PCA and Correlated Noise
It is now common to have a modest to large number of features on individuals with complex diseases. Unsupervised analyses, such as clustering with and without preprocessing by Principle Component Analysis (PCA), is widely used in practice to uncover subgroups in a sample. However, in many modern stu...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | Journal of statistical computation and simulation. - 1999. - 94(2024), 10 vom: 16., Seite 2291-2319
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| 1. Verfasser: |
Lippitt, William
(VerfasserIn) |
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| Weitere Verfasser: |
Carlson, Nichole E,
Arbet, Jaron,
Fingerlin, Tasha E,
Maier, Lisa A,
Kechris, Katerina |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2024
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| Zugriff auf das übergeordnete Werk: | Journal of statistical computation and simulation
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| Schlagworte: | Journal Article
Correlation
Gaussian mixture models
PCA
Unsupervised filtering
Variance as relevance |
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