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An Innovative Clustering Approach To Market Segmentation For Improved Price Prediction, Donghui Shi, Jian Guan, Jozef Zurada, Alan S. Levitan

Journal of International Technology and Information Management

A main obstacle to accurate prediction is often the heterogeneous nature of data. Existing studies have pointed to data clustering as a potential solution to reduce heterogeneity, and therefore increase prediction accuracy. This paper describes an innovative clustering approach based on a novel adaptation of the Fuzzy C-Means algorithm and its application to market segmentation in real estate. Over 15,000 actual home sales transactions were used to evaluate our approach. The test results demonstrate that the accuracy in price prediction shows notable improvement for some clustered market segments. In comparison with existing methods our approach is simple to implement. It …