Application of Fuzzy Cluster Analysis to the Classification of Real Estate

王一然 WYR


基于传统的Fuzzy等价关系聚类法,由Fuzzy相似矩阵构建Fuzzy等价矩阵,对传递闭包采用Warshall算法求解,并选择不同置信水平下的分类,利用偏差度得到最优聚类.结合北京市朝阳区近3个月新开楼盘的数据,选择可靠性指标,在最佳置信水平的基础上对其进行最优聚类,实验结果与事实吻合. Base on the traditional fuzzy equivalence relation clustering, the fuzzy equivalence matrix is structured by the fuzzy similarity matrix, and it solves the transitive closure with the Warshall algorithm, then we choose the classification under the different credit levels. at last, we get the best clustering by the degree of deviation. This paper combine the real estate data of the past 3 months in Beijing of Chaoyang District, then choose reliability indexes, and make the best clustering base on the optimum credit level, and the result dovetails nicely with actual situation.


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