Research On Application Of K-Means Clustering Algorithm In Management Of Banking Manager In Personal Business

With the development of network technology and computer application, we have more and more electronic data. "More data but less knowledge" is becoming more and more serious. Data mining technology opens the way for the problem, and substantial achievements have been made in data mining technology researching and promoting.In recent years, banking in China has made excellent achievements in informatization construction, but the commercial application of data mining technology is still in its exploratory stage.The thesis firstly discusses the client subdivision and the management of banking manager in personal business in commercial bank theoretically, thus showing the theoretical basis of subdividing the banking manager in personal business. Secondly, the thesis makes analysis on K-means clustering algorithm and shows its practical application difficulties. Finally, according to model CRISP-DM and SEMMA, the thesis brings up 6 stages under positive analysis, and gives a detailed account of each stage. With the help of SAS software, K-means clustering algorithm can be realized to improve the local optima through 3 methods to choose different initial condensation point.The thesis solves the practical application problem of management of banking manager in personal business on the basis of K-means clustering algorithm, and makes a study on the data mining application theory and technology in commercial bank, which are hoped to be conducive to the promotion of data mining technology in China.