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Study of Recognition Approach for Specific Sample Points in High Dimension Space

机译:高维空间中特定样本点的识别方法研究

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Based on secondary analysis techniques to identify specific sample point using partial least-squares analysis method, the recognition method of specific sample point of two-dimensional floor plan of ellipse T2 was extended to three-dimensional figure of ellipsoid T2 and high-dimensional space of hyper- ellipsoid T2. Another Identification method of specific sample point making use of hierarchical diagram in high-dimensional space based on hierarchical clustering method was proposed at the same time. The recognition method of specific sample point had great significance on research areas of data mining, machine learning and pattern recognition while eliminating samples generated due to random factors and refining mathematical models. Empirical analysis of the five kinds of identification method was accomplished using ecological data of the 56 observation sites along the Bohai Sea coastal zone.
机译:在二次分析技术的基础上,采用偏最小二乘分析法识别特定样本点,将椭圆T2的二维平面图的特定样本点的识别方法扩展到椭圆形T2的三维图形和二维空间的高维空间。超椭球体T2。同时提出了一种基于层次聚类的高维空间层次图特定样本点识别方法。特定样本点的识别方法在数据挖掘,机器学习和模式识别等研究领域中具有重要意义,同时消除了由于随机因素而产生的样本并完善了数学模型。利用渤海沿岸56个观测点的生态数据对五种识别方法进行了实证分析。

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