基于改进决策树算法的汽车销售数据挖掘

Car Sales Data Mining Based on Improved Decision Tree Algorithm

决策树分类算法是数据挖掘中最基本也是最重要的算法之一。目前,数据挖掘技术被广泛应用在商业领域中。在汽车产品销售系统中,引入数据挖掘技术,可以为汽车销售的经营决策提供科学依据。本文收集某汽车品牌安徽地区近一年的销售数据进行集成和数据预处理;之后采用数据挖掘技术中的改进决策树算法,对汽车销售数据仓库分析和应用,预测影响汽车的销售的主要因素,从而制定汽车的营销策略,帮助企业得到更好的收益。

Decision tree classification algorithm is one of the most basic and important algorithms in data mining. At present,data mining technology has been widely used in the commercial field. The introduction of data mining technology in the automobile product sales system can provide scientific basis for the decision making of automobile sales. In this paper,some automobile brand sales data are collected in Anhui for nearly a year for integration and data preprocessing,which are then analyzed and applied using data mining improved decision tree algorithm to make a prediction of the main factors influencing the automobile sales and thus make marketing strategies to help enterprises to get better returns.