首页> 外国专利> GENERATING METHOD OF TWO CLASS CLASSIFICATION PREDICTION MODEL, COMPUTER-READABLE RECORDING MEDIUM HAVING PROGRAM FOR GENERATING CLASSIFICATION PREDICTION MODEL AND GENERATING DEVICE OF TWO CLASS CLASSIFICATION PREDICTION MODEL

GENERATING METHOD OF TWO CLASS CLASSIFICATION PREDICTION MODEL, COMPUTER-READABLE RECORDING MEDIUM HAVING PROGRAM FOR GENERATING CLASSIFICATION PREDICTION MODEL AND GENERATING DEVICE OF TWO CLASS CLASSIFICATION PREDICTION MODEL

机译:两种分类预测模型的生成方法,具有该分类预测模型的生成装置和计算机可读记录介质的程序,两种分类预测模型的生成装置

摘要

A two-class classification/prediction model is generated in a simple operation by performing two-class classification with a classification rate substantially close to 100%. The two-class classification/prediction model is generated by a) obtaining a discriminant function for classifying a training sample set into two predetermined classes on the basis of an explanatory variable generated for each sample contained in the training sample set, b) calculating a discriminant score for each training sample by using the obtained discriminant function, c) determining, based on the calculated discriminant score, whether the training sample is correctly classified or not, d) determining a misclassified-sample region based on maximum and minimum discriminant scores taken from among misclassified samples in the training sample set, e) constructing a new training sample set by extracting the training samples contained in the misclassified-sample region, and f) repeating a) to e) for the new training sample set.
机译:通过以大致接近100%的分类率执行两类分类,以简单的操作来生成两类分类/预测模型。通过以下方法生成两类分类/预测模型:a)根据针对包含在训练样本集中的每个样本生成的解释变量,获得用于将训练样本集分为两个预定类别的判别函数; b)计算判别式使用获得的判别函数对每个训练样本进行评分,c)根据计算出的判别分数确定训练样本是否正确分类,d)根据从中获取的最大和最小判别分数确定分类错误的样本区域在训练样本集中的错误分类样本中,e)通过提取包含在错误分类样本区域中的训练样本来构建新的训练样本集,以及f)对新的训练样本集合重复a)到e)。

著录项

  • 公开/公告号KR101126390B1

    专利类型

  • 公开/公告日2012-03-29

    原文格式PDF

  • 申请/专利权人

    申请/专利号KR20107013416

  • 发明设计人 유타 고타로우;

    申请日2007-12-18

  • 分类号G06N5/04;G06F15/18;G06N3/00;

  • 国家 KR

  • 入库时间 2022-08-21 17:08:24

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