两种数据挖掘技术在预测顾客满意度中的对比研究

分类发现是数据挖掘的重要内容,贝叶斯分类和决策树在数据挖掘中应用相当广泛,它们是生成分类器的两种有效方法。文章分别用两种方法对顾客满意度进行分类及预测,并将两种方法进行比较分析,认为用决策树分类法来预测顾客满意度具有简洁、高效等特点。

Comparative Research on Two Kinds of Data Mining Technologies in Forecasting the Customer Degree of Satisfaction

Classification discovery is an important task in Data Mining,and the Bayesian classification and the decision tree in data mining are applied quite wildly.They are the two effective methods to produce the sorter.This article separately uses two methods to classify and forecast the customer degree of satisfaction,and compares and analyze the two methods,Decision tree is considered to forecast the customer degree of satisfaction its characteristic of simplicity and efficiency.