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Assessment of the accuracy of a learn model machines

机译:评估学习模型机器的准确性

摘要

The computer-readable medium on the executable instructions are stored, which performs cause a processor, a computer implemented method for assessing the accuracy of a learn model machines, to carry out the process comprising:the receiving a plurality of requests for a first content element;the assignment of a first part of the received requests for the first content element to a first group and the assigning of the rest of the received requests for the first content element to a second group;the use of a machines learn model for a request which has been allocated to the first group, in order to variants of a plurality of a variant of the first content element to the representation to be selected in response to said query request;the use of a statistical model for a request which has been allocated to the second group, in order to the plurality of variants of a variant of the first content element for the representation in response to said query request; andthe obtaining information about the accuracy of the machines learn model, in that performance data for variants of the first, by means of the machines learn model selected content element with performance data for variants of the first, by means of the statistical model selected content element are compared.
机译:可执行指令上的计算机可读介质被存储,该计算机可读介质使处理器,用于评估学习模型机器的准确性的计算机实现的方法执行以执行该过程,该过程包括:接收对第一内容元素的多个请求。 ;将接收到的对第一内容元素的请求的第一部分分配给第一组;将接收到的对第一内容元素的请求的其余部分分配给第二组;使用机器学习请求的模型为了响应所述查询请求而选择第一内容元素的多个变体到表示形式的变体,该第一内容元素已被分配给第一组;将统计模型用于已分配的请求到第二组,以响应于所述查询请求的表示的第一内容元素的变体的多个变体;以及获得关于机器学习模型的准确性的信息,其中,通过机器的学习,通过统计模型选择的内容元素,利用机器学习模型选择的内容元素与模型选择的内容元素之间的性能数据比较。

著录项

  • 公开/公告号DE212017000012U1

    专利类型

  • 公开/公告日2018-04-26

    原文格式PDF

  • 申请/专利权人 GOOGLE LLC;

    申请/专利号DE20172100012U

  • 发明设计人

    申请日2017-01-24

  • 分类号G06N5/00;

  • 国家 DE

  • 入库时间 2022-08-21 12:33:21

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