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- W2134858082 abstract "In privacy preserving classification, when data is stored in a centralized database and distorted using a randomization-based technique, we have information loss and reduced accuracy of classification. This paper presents a new approach to privacy preserving classification for centralized data based on Emerging Patterns. The presented solution gives higher accuracy of classification than a decision tree proposed in the literature, especially for high privacy. Effectiveness of this solution has been tested on real data sets and presented in this paper." @default.
- W2134858082 created "2016-06-24" @default.
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- W2134858082 date "2009-12-01" @default.
- W2134858082 modified "2023-09-23" @default.
- W2134858082 title "Privacy Preserving Classification with Emerging Patterns" @default.
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- W2134858082 doi "https://doi.org/10.1109/icdmw.2009.82" @default.
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