Feature extraction by the SCoTLASS: an illustrative example

Bartkowiak, Anna and Trendafilov, Nickolay (2005). Feature extraction by the SCoTLASS: an illustrative example. In: Klopotek, Mieczyslaw A; Wierzchen, Slawomir T. and Trojanowski, Krzysztof eds. Intelligent Information Processing and Web Mining. Advances in Intelligent and Soft Computing (31). Berlin: Springer, pp. 3–11.

URL: http://www.springer.com/engineering/book/978-3-540...

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 preoperties of the SCoTLASS method applied to the yeast genes data investicaged in (Bartkowiak et al., 2003, 2004). All the derived features have really a simple meaningful structue: each new feature is spanned by two original variables belonging to the same block.

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• Item ORO ID
• 22565
• Item Type
• Book Section
• ISBN
• 3-540-25056-5, 978-3-540-25056-2
• Extra Information
• Proceedings of the International IIS: IIPWM´05 Conference held in Gdansk, Poland, June 13-16, 2005
• Keywords
• artificial intelligence; data mining; machine learning
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 2005 Springer-Verlag
• Depositing User
• Sarah Frain