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In this paper, a privacy preserving classification algorithm based random diffusion map is presented. We first alter the selection of the parameter dimension d and metaparameter fixed value ?? for satisfying the security of privacy-preserving classification. Further the sensitive attributes are embedded into random(even higher) dimension feature space using random diffusion map, thus the sensitive...
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