Decision Tree-based Data Mining Algorithm And Its Practical Application

Data mining is to extract hidden from the database with information on the potential value of the process is a new data analysis techniques. It is extracted from a large number of data out of the potential,unknown useful information, patterns and trends. The aim is to improve the market decision-making ability to detect unusual patterns,based on past experience,predict future trends and so on. At present,has been widely used in finance,insurance,government,education,transportation,and defense and other fields.This paper is to study the decision tree data mining algorithms and decision tree algorithm in a specific customer relationship management systems research and analysis. First,the generation of data mining technology and development status of done a broad exposition introduced the concept of data mining,main content,patterns and key issues, as well as data mining applications and development;and then right in the decision tree data mining techniques to do a detailed description,presented in the classic decision tree algorithm for mining. Finally,for the modern enterprise management,customer relationship management issues,through data mining technology in a large number of historical data to carry out excavation analysis,combined with ID3 algorithm to segment customers,tap a different customer base and operational features,the company recommends against tendency to a higher loss groups,and integrating the customer's customer base features correspond to adopt a targeted customer retention strategies. In the commercial application of theoretical knowledge,this paper carried out a meaningful exploration and attempts.