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Lazy Approach to Privacy Preserving Classification with Emerging Patterns

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Emerging Intelligent Technologies in Industry

Part of the book series: Studies in Computational Intelligence ((SCI,volume 369))

Abstract

In privacy preserving classification when data is stored in a centralized database and distorted using a randomization-based technique emerging patterns can be used to contrast classes. We present the new approach to privacy preserving classification for centralized data based on Emerging Patterns. In contrast to previous works, we use a lazy approach based on DeEPs to classification. Effectiveness of this solution has been tested and presented in this paper.

Work financially supported from Ministry of Science and Higher Education founds reserved for science as a research project N N516 070437.

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Authors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland

    Piotr Andruszkiewicz

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  1. Piotr Andruszkiewicz
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Editors and Affiliations

  1. Institute of Computer Science Faculty of Electronics and Information Technology, Warsaw University of Technology, ul.Nowowiejska 15/19, 00-665, Warsaw, Poland

    Dominik Ryżko , Henryk Rybiński , Piotr Gawrysiak  & Marzena Kryszkiewicz , ,  & 

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Andruszkiewicz, P. (2011). Lazy Approach to Privacy Preserving Classification with Emerging Patterns. In: Ryżko, D., Rybiński, H., Gawrysiak, P., Kryszkiewicz, M. (eds) Emerging Intelligent Technologies in Industry. Studies in Computational Intelligence, vol 369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22732-5_21

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  • DOI: https://doi.org/10.1007/978-3-642-22732-5_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22731-8

  • Online ISBN: 978-3-642-22732-5

  • eBook Packages: EngineeringEngineering (R0)

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