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Variable selection and the interpretation of principal subspaces

✍ Scribed by Jorge F. C. L. Cadima; Ian T. Jolliffe


Book ID
111762321
Publisher
Springer-Verlag
Year
2001
Tongue
English
Weight
240 KB
Volume
6
Category
Article
ISSN
1085-7117

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Variable selection in large environmenta
✍ Jacquelynne R. King; Donald A. Jackson πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 117 KB πŸ‘ 2 views

In many large environmental datasets redundant variables can be discarded without the loss of extra variation. Principal components analysis can be used to select those variables that contain the most information. Using an environmental dataset consisting of 36 meteorological variables spanning 37 y