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首页> 外文期刊>Journal of Information and Organizational Sciences >An Algorithm for Detecting the Principal Allotment among Fuzzy Clusters and Its Application as a Technique of Reduction of Analyzed Features Space Dimensionality
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An Algorithm for Detecting the Principal Allotment among Fuzzy Clusters and Its Application as a Technique of Reduction of Analyzed Features Space Dimensionality

机译：模糊聚类中主分配的检测算法及其在减少特征空间维数中的应用

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This paper describes a modification of a possibilistic clustering method based on the concept of allotment among fuzzy clusters. Basic ideas of the method are considered and the concept of a principal allotment among fuzzy clusters is introduced. The paper provides the description of the plan of the algorithm for detection principal allotment. An analysis of experimental results of the proposed algorithm’s application to the Tamura’s portrait data in comparison with the basic version of the algorithm and with the NERFCM-algorithm is carried out. A methodology of the algorithm’s application to the dimensionality reduction problem is outlined and the application of the methodology is illustrated on the example of Anderson’s Iris data in comparison with the result of principal component analysis. Preliminary conclusions are formulated also.
机译：本文描述了一种基于模糊聚类分配概念的可能性聚类方法的改进。考虑了该方法的基本思想，介绍了模糊聚类之间的主要分配概念。本文介绍了用于检测主体分配算法的计划。与该算法的基本版本和NERFCM算法进行了比较，分析了该算法应用于田村人像数据的实验结果。概述了该算法在降维问题中的应用方法，并与主要成分分析结果相比较，在安德森（Anderson）的Iris数据示例中说明了该方法的应用。还得出初步结论。

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