有指导的数据挖掘在心脏病风险评价中的应用

Supervised learning based data mining technology with its application to heart diseases risk detection

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。作者用心脏病数据集范例来解释有指导学习的过程。实验表明患心脏病病人的某些属性特征和患心脏病风险的大小有较大关系。数据挖掘的结果对于医生临床诊断有很重要的意义。

This paper introduces concept of data mining, and presents two methods of data mining： supervised learning and unsupervised learning.The author uses a intance about heart disease and explain the process of supervised learning.The experiment show that some attributes of patients are strongly related to heart diseases risk levels.The result of data mining is much significant to doctors＇ clinical diagnosis.