DocumentCode :
3306435
Title :
UCK-means :A customized K-means for clustering uncertain measurement data
Author :
Peng Yu ; Luo Qinghua ; Peng Xiyuan
Author_Institution :
Autom. Test & Control Inst., Harbin Inst. of Technol., Harbin, China
Volume :
2
fYear :
2011
fDate :
26-28 July 2011
Firstpage :
1196
Lastpage :
1200
Abstract :
Due to some reasons such as transmitting error or outdated or imprecise measurement, data uncertainty is an inherent property in wireless sensor networks or in LXI test framework. When we apply data mining techniques to these uncertain data, we must consider the uncertainty to get better data mining results. At present, most of uncertain data clustering methods assume the probability density functions or probability distribution function of whole data is available. However, in many real applications, this piece of information is rarely available. Only limited uncertain information may be available, such as the standard deviation. In this paper, we adopt a more realistic assumption that the standard deviation of individual measurement data is available, and propose a new uncertain distance computing method between multi-dimensional uncertain data. In addition, we propose an uncertain customized data clustering algorithm based on the classical K-means to process the multi-dimensional uncertain data. Experiment results show that the uncertain clustering algorithm can produce better results with lower complexity.
Keywords :
data mining; pattern clustering; statistical distributions; uncertainty handling; LXI test framework; UCK mean; customized K-means; data mining techniques; data uncertainty; individual measurement data; multicdimensional uncertain data; probability density functions; probability distribution function; realistic assumption; uncertain customized data clustering algorithm; uncertain data clustering methods; uncertain distance computing method; wireless sensor networks; Accuracy; Clustering algorithms; Correlation; Data mining; Iris; Temperature measurement; Uncertainty; Wireless Sensor Network; data clustering; data mining; uncertain data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
Type :
conf
DOI :
10.1109/FSKD.2011.6019639
Filename :
6019639
Link To Document :
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