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Importance of TDS Attribute in Computer Assisted Classification of Melanocytic Skin Lesions

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Intelligent Information Processing and Web Mining

Part of the book series: Advances in Soft Computing ((AINSC,volume 31))

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Abstract

In the paper the new algorithm and results of its application to designation the importance of the TDS attribute in identifying the melanocytic skin lesions are described. The algorithm consists of decision table, TDS belief net, and the nearest neighbor method applied to the bases, which was obtained by reduction the number of attributes from thirteen to four. The obtained results show that this algorithm is very promising.

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Authors and Affiliations

  1. Rzeszów University of Technology, ul. W. Pola 2, 35-959, Rzeszów, Poland

    Aleksander Sokołowski

Authors
  1. Aleksander Sokołowski
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Editors and Affiliations

  1. Institute of Computer Sciences, Polish Academy of Sciences, ul. Ordona 21, 01-237, Warszawa, Poland

    Mieczysław A. Kłopotek , Sławomir T. Wierzchoń  & Krzysztof Trojanowski ,  & 

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© 2005 Springer-Verlag Berlin Heidelberg

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Sokołowski, A. (2005). Importance of TDS Attribute in Computer Assisted Classification of Melanocytic Skin Lesions. 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_59

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  • DOI: https://doi.org/10.1007/3-540-32392-9_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25056-2

  • Online ISBN: 978-3-540-32392-1

  • eBook Packages: EngineeringEngineering (R0)

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