Method for constructing decision tree based on differential privacy protection
A differential privacy and decision tree technology, applied in digital data protection, instrumentation, electrical digital data processing, etc., can solve the problems of inefficient selection methods and depletion of privacy budget, so as to protect privacy, improve accuracy, and reduce rapid consumption Effect
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[0019] The present invention will be described in detail below in conjunction with the examples.
[0020] The present invention provides a method based on differential privacy protection decision tree, which aims at the differential privacy protection of the classic greedy decision tree C4. A protection mechanism alters this answer in a way that preserves the privacy of everyone in the dataset. The present invention comprises the following steps:
[0021] 1) Use Bernoulli (Bernoulli) random sampling principle to sample the original data set with sampling probability p to obtain a data set sample, and the obtained data set satisfies ln(1+p(e ε -1))- Differential privacy:
[0022] Perform Bernoulli random sampling on the original data set with the assumed sampling probability p, put the selected samples into the spatial samples, otherwise discard them, and calculate the privacy budget ε required to build the entire decision tree under the sampling probability p p . Among the...
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