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Support Feature Machine for DNA Microarray Data

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Book cover Rough Sets and Current Trends in Computing (RSCTC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6086))

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Abstract

Support Feature Machines (SFM) define useful features derived from similarity to support vectors (kernel transformations), global projections (linear or perceptron-style) and localized projections. Explicit construction of extended feature spaces enables control over selection of features, complexity control and allows final analysis by any classification method. Additionally projections of high-dimensional data may be used to estimate and display confidence of predictions. This approach has been applied to the DNA microarray data.

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Author information

Authors and Affiliations

  1. Department of Informatics, Nicolaus Copernicus University, Grudzia̧dzka 5, 87-100, Toruń, Poland

    Tomasz Maszczyk & Włodzisław Duch

Authors
  1. Tomasz Maszczyk
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  2. Włodzisław Duch
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Editor information

Editors and Affiliations

  1. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Marcin Szczuka

  2. ICS, Warsaw University of Technology,,  

    Marzena Kryszkiewicz

  3. Department of Applied Computer Science, University of Winnipeg, R3B 2E9, Winnipeg, Manitoba, Canada

    Sheela Ramanna

  4. Dept. of Computer Science, The University of Wales, Aberystwyth, UK

    Richard Jensen

  5. Harbin Institute of Technology, PO Box 458, 150006, Harbin, China

    Qinghua Hu

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Maszczyk, T., Duch, W. (2010). Support Feature Machine for DNA Microarray Data. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds) Rough Sets and Current Trends in Computing. RSCTC 2010. Lecture Notes in Computer Science(), vol 6086. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13529-3_20

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  • DOI: https://doi.org/10.1007/978-3-642-13529-3_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13528-6

  • Online ISBN: 978-3-642-13529-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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