Information technology of data clustering in the time interval of observation
Abstract
Cluster analysis is an important task of data mining. The use of clustering techniques allows to understand the structure of multidimensional data; to simplify further processing using different methods of analysis for each cluster; reduce the original sample data, leaving the most typical representatives of each group; detect novelty, atypical objects that can not be attached to any of the classes; formulate or test hypotheses based on the results. In this article а new approach to the selection of groups of objects that are similar to each other on a set of features that changing over time has been proposed. Information technology of quality assessment and improvement of the stability of clustering has been developed. The results of practical implementation of the proposed technology to data of hydrochemical monitoring of ater objects in the area with high technological load have been presented.References
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