A literature study on clustering the uncertainty data
Journal Title: Indian Journal of Computer Science and Engineering - Year 2016, Vol 7, Issue 3
Abstract
Clustering is one of the important topics in data mining. The purpose of clustering is to group the similar data items. Clustering the uncertainty data is not an easy task but an essential task in data mining. Uncertain data represents the unexpected outcome. It is mostly found in the area of sensor networks. The uncertain data may have numerical and categorical data. For numerical clustering, the distance measure is based on geometric concepts such as Euclidean distance or Manhattan distance. Since the categorical data contains nominal values like [good, bad], [low, medium, high],the geometric distance measures are not applicable for categorical or nominal data. We used the numerical data (i.e.) Gas sensor data. From the literature in this field, it is noticed that very few attempts had been made for clustering gas sensor dataset using few methods and discuss the same in this paper.
Authors and Affiliations
S. SATHAPPAN , Dr. D. C. TOMAR
Keywords
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