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    • 7. 发明授权
    • Distributed decision tree training
    • 分布式决策树训练
    • US08543517B2
    • 2013-09-24
    • US12797430
    • 2010-06-09
    • Jamie ShottonMihai-Dan BudiuAndrew William FitzgibbonMark FinocchioRichard E. MooreDuncan Robertson
    • Jamie ShottonMihai-Dan BudiuAndrew William FitzgibbonMark FinocchioRichard E. MooreDuncan Robertson
    • G06F15/18
    • G06K9/6282
    • A computerized decision tree training system may include a distributed control processing unit configured to receive input of training data for training a decision tree. The system may further include a plurality of data batch processing units, each data batch processing unit being configured to evaluate each of a plurality of split functions of a decision tree for respective data batch of the training data, to thereby compute a partial histogram for each split function, for each datum in the data batch. The system may further include a plurality of node batch processing units configured to aggregate the associated partial histograms for each split function to form an aggregated histogram for each split function for each of a subset of frontier tree nodes and to determine a selected split function for each frontier tree node by computing the split function that produces highest information gain for the frontier tree node.
    • 计算机化决策树训练系统可以包括配置成接收用于训练决策树的训练数据的输入的分布式控制处理单元。 该系统还可以包括多个数据批处理单元,每个数据批处理单元被配置为评估用于训练数据的相应数据批的决策树的多个分离函数中的每一个,从而计算每个 分割功能,用于数据批处理中的每个数据。 该系统可以进一步包括多个节点批量处理单元,其被配置为针对每个分割函数聚合相关联的部分直方图,以形成用于边界树节点的子集中的每一个的每个分割函数的聚合直方图,并且为每个分割函数确定每个 边缘树节点通过计算为边界树节点产生最高信息增益的分割函数。