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http://dx.doi.org/10.15207/JKCS.2017.8.11.103

A Clustering Algorithm for Handling Missing Data  

Lee, Jong Chan (Dept. of Internet, Chungwoon University)
Publication Information
Journal of the Korea Convergence Society / v.8, no.11, 2017 , pp. 103-108 More about this Journal
Abstract
In the ubiquitous environment, there has been a problem of transmitting data from various sensors at a long distance. Especially, in the process of integrating data arriving at different locations, data having different property values of data or having some loss in data had to be processed. This paper present a method to analyze such data. The core of this method is to define an objective function suitable for the problem and to develop an algorithm that can optimize this objective function. The objective function is used by modifying the OCS function. MFA (Mean Field Annealing), which was able to process only binary data, is extended to be applicable to fields with continuous values. It is called CMFA and used as an optimization algorithm.
Keywords
Missing data; Clustering; Continuous mean field theory; OCS objective function; Optimization algorithm;
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