Abstract
Derivation of new features of observed variables has two important goals: reduction of dimensionality and de-noising. A desired property of the derived new features is their meaningful interpretation. The SCoTLASS method (Jolliffe, Trendafilov and Uddin, 2003) offers such possibility.
We explore the properties of the SCoTLASS method applied to the yeast genes data investigated in (Bartkowiak et al., 2003, 2004). All the derived features have really a simple meaningful structure: each new feature is spanned by two original variables belonging to the same block.
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References
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Bartkowiak, A., Trendafilov, N.T. (2005). Feature Extraction by the SCoTLASS: An Illustrative Example. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32392-9_1
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DOI: https://doi.org/10.1007/3-540-32392-9_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25056-2
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