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OPTIMIZATION APPARATUS, NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM FOR STORING OPTIMIZATION PROGRAM, AND OPTIMIZATION METHOD

机译:优化装置,用于存储优化程序的非暂态计算机可读存储介质和优化方法

摘要

A method includes: partitioning learning data containing objective variables and explanatory variables into a plurality of subsets of data; executing regularization processing on first data in each of the partitioned subsets, and extracting a first element equal to zero; extracting, as a candidate, each model where an error ratio between first multiple regression and second multiple regression is equal to or more than a predetermined value, the first multiple regression being a result of multiple regression on second data which is test data in each of the partitioned subsets and is for use to calculate the error ratio of the learning data, the second multiple regression being a result of multiple regression on third data obtained by excluding the first element from the second data; and outputting a model where zero is substituted for an element that takes zero a predetermined or larger number of times in the candidate.
机译:一种方法,包括:将包含目标变量和解释变量的学习数据划分为多个数据子集;对每个分区子集中的第一数据进行正则化处理,提取等于零的第一元素;作为候选,提取其中第一多重回归和第二多重回归之间的误差比等于或大于预定值的每个模型,第一多重回归是对作为每个数据的测试数据的第二数据进行多重回归的结果。分割后的子集,用于计算学习数据的错误率,第二多元回归是对第三数据进行多元回归的结果,该第三数据是通过从第二数据中排除第一元素而获得的;并输出一个模型,其中用零代替在候选中占预定次数或更大次数的零的元素。

著录项

  • 公开/公告号US2020184375A1

    专利类型

  • 公开/公告日2020-06-11

    原文格式PDF

  • 申请/专利权人 FUJITSU LIMITED;

    申请/专利号US201916690335

  • 发明设计人 TAKUYA OHWA;HIDETOSHI MATSUOKA;

    申请日2019-11-21

  • 分类号G06N20;G06F17/18;G06F17/50;

  • 国家 US

  • 入库时间 2022-08-21 11:27:34

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