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Design tariff policy for brokerage service clients based on adaptive clustering methods

The article is devoted to one of analysis tasks of the data mining. Authors introduce the methodology of the adaptive clustering based on integration and modification of popular methods Fuzzy Cmeans and MST. Also in the article new methods of post-clustering are described, which can reduce time for research. The methodology compares with existing approaches (K-means and Self-Organizing Maps). The article gives an example of its practical usage for designing tariff policy in the field of brokerage service.