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Clustering Structure Analysis in Time-Series Data With Density-Based Clusterability Measure 被引量:6
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作者 juho jokinen Tomi Raty Timo Lintonen 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2019年第6期1332-1343,共12页
Clustering is used to gain an intuition of the struc tures in the data.Most of the current clustering algorithms pro duce a clustering structure even on data that do not possess such structure.In these cases,the algor... Clustering is used to gain an intuition of the struc tures in the data.Most of the current clustering algorithms pro duce a clustering structure even on data that do not possess such structure.In these cases,the algorithms force a structure in the data instead of discovering one.To avoid false structures in the relations of data,a novel clusterability assessment method called density-based clusterability measure is proposed in this paper.I measures the prominence of clustering structure in the data to evaluate whether a cluster analysis could produce a meaningfu insight to the relationships in the data.This is especially useful in time-series data since visualizing the structure in time-series data is hard.The performance of the clusterability measure is evalu ated against several synthetic data sets and time-series data sets which illustrate that the density-based clusterability measure can successfully indicate clustering structure of time-series data. 展开更多
关键词 CLUSTERING EXPLORATORY data analysis time-series UNSUPERVISED LEARNING
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