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Differentially private machine learning using a random forest classifier

机译:使用随机森林分类器的差异私有机器学习

摘要

A request from a client is received to generate a differentially private random forest classifier trained using a set of restricted data. The differentially private random forest classifier is generated in response to the request. Generating the differentially private random forest classifier includes determining a number of decision trees and generating the determined number of decision trees. Generating a decision tree includes generating a set of splits based on the restricted data, determining an information gain for each split, selecting a split from the set using an exponential mechanism, and adding the split to the decision tree. The differentially private random forest classifier is provided to the client.
机译:接收到来自客户端的请求,以生成使用一组受限数据训练的差分私有随机森林分类器。响应于该请求,生成差异私有随机森林分类器。生成差异私有随机森林分类器包括确定决策树的数量并生成确定数量的决策树。生成决策树包括基于受限数据生成一组拆分,确定每个拆分的信息增益,使用指数机制从该拆分中选择拆分,以及将拆分添加到决策树。将差异私有随机森林分类器提供给客户端。

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