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Verification of Clustering Accuracy by Applying Direction-Based Method and Data Conversion

机译:通过应用基于方向的方法和数据转换来验证聚类准确性

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In this study, the process of clustering into a group with similar characteristics is shown through pattern analysis, and the similarity is examined whether this group has homogeneity. A direction-based method for clustering the time series data is introduced, and the grouping process is carried out through the direction setting by up or down and the logical operations thereafter. The similarity is verified by comparing the parts within the group after clustering. For more effective verification, data conversion, a data homogenization process, is performed. MAD, MSE, MPSE and TS are reviewed as similarity indicators. For data such as time series data, MPSE and TS, which are scale-independent measurements, are recommended.
机译:在本研究中,通过模式分析显示将聚类为具有相似特征的组的过程,检查该组是否具有均匀性。 引入了用于聚类时间序列数据的基于方向的方法,并且通过向上或向下通过方向设置和此后的逻辑操作来执行分组处理。 通过比较群集后组内的部件来验证相似度。 为了更有效验证,执行数据转换,数据均质化过程。 MAD,MSE,MPSE和TS被视为相似性指标。 对于诸如时间序列数据,推荐的MPSE和TS的数据,建议使用比例级别的测量值。

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