数据挖掘技术在人寿保险数据库中的应用

The Application of Data Mining Technology to Life Insurance Dataset Analysis

本文讲述了什么是数据挖掘,以及数据挖掘的两种策略:有指导和无指导学习。本文用IDA分析器指导一组寿险人群数据集范例来进行学习。实验表明未购买寿险的人群的某些属性特征和年龄、收入有较大关系。数据挖掘的结果对于寿险销售人员提高效率有很重要的意义,特别指出了最有可能购买寿险的人群所具有的特点。

This paper introducel concept of data mining, and presents two methods of data mining： supervised learning and unsupervised learning. An instance of life insurance dataset was used to explain the process of supervised learning. The experiment showed that among those who had purchased life insurances there are some common attributes such as age and incomes. The result of data mining was much significant for the insurance sales representatives to improve efficiency and focused on the specific people who had greater probability to buy life insurances.