The Application Of Clustering Analysis Based On Facter Analysis And Rough Set In Dividing The City

With the pace of reform and opening up, our country making big strides forward on the road of economic development, the people of the motherland also by poverty came to overall well-off, achieved a historic leap. At the same time, the city of our country also in according to their own route, active and rapid development, Beijing, Shanghai is a representative city of China, has embarked on a road of international metropolis. However, in addition to these cities in the development of better, China still has a lot of urban public infrastructure construction is lagging behind, economic development is far lower than the national average standard, how to make better policy allows the city to obtain better development is a country's future development to test one of the worrying problem, and to be better for different cities to develop their own development plan, need to divide the city.Cluster analysis is an analysis technique in data mining, by judging between data object distance or correlation, data objects which are close to the condensed into clusters, the traditional clustering methods have many advantages, inevitably, there are some disadvantages, when dealing with complex high dimensional data may exist all kinds of problems. Therefore, this paper presents a new clustering model, using factor analysis to reduce the dimensionality of data set, and then use the rough set lower approximation set thought to avoid the traditional clustering method, the boundary is fuzzy. Finally, based on the idea of clustering analysis for data processing based on rough set.In this paper by the model on the urban statistical yearbook of China 2013 "provided by the data analysis, it is concluded that the classification results of a city and the result with the ordinary cluster analysis results were compared, to demonstrate the model's effectiveness.