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A New Filter Method of Specific Sample Points Based on Partial Least-Squares Analysis

机译:基于偏最小二乘分析的特定采样点的新滤波方法

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Specific sample point was a kind of noise that must be excluded from original data in the process of data mining and machine learning. A new filter method of specific sample points based on partial least-squares analysis was introduced in this paper. Two conceptions of true and false specific sample points were given and their relationship was elaborated in detail. The paper defined the critical value distinguishing true and false specific sample points and presented the critical formula. A novel method for identifying true and false specific sample points was described by using ellipse T~2 diagram, ellipsoid T~2 and scatter diagram of the principal component. Discrimination and filter method of specific sample points took great effect on eliminating samples created by random factors and purifying ultimate model.
机译:具体的采样点是一种噪声,必须在数据挖掘和机器学习过程中从原始数据中排除。本文介绍了一种基于局部最小二乘分析的特定样本点的新滤波方法。给出了真实和虚假特定样本点的两个概念,并详细阐述了他们的关系。本文定义了区分真实和虚假特定样本点的关键值,并呈现了关键公式。通过使用椭圆T〜2图,椭圆形T〜2和主成分的散点图描述了一种识别真特定采样点的新方法。特定样本点的歧视和滤波方法对消除随机因子和净化终极模型产生的样本产生了很大的影响。

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