摘要
数据开采是利用现代统计学知识和计算知识从大型数据库中发现潜在的有用模式的学科。可以说,数据开采的目的和数据开采中使用的方法,覆盖了古典的统计学应用范畴。然而,统计学和数据开采在哲学上和使用方法上都有许多的差别。文中描述统计学和数据开采方法在知识发现上的差异,指出统计学和数据开采可通过彼此学习和互相使用来得到发展。
Data mining can be regarded as a collection of methods for discovery useful pattern from large databases. The aims of data mining and some of its methods overlap with those of classical statistics. However, there are some philosophical and methodological differences. In this paper, we describe and compare these differences, and give an overview Of the area and conclude that statisticians and data miners can profit by studying each Other s methods.
出处
《计算机工程与应用》
CSCD
北大核心
2000年第5期15-17,共3页
Computer Engineering and Applications
基金
国家自然科学基金
关键词
数据开采
统计学
决策树
数据库
Classification
Data mining
statistics
decision trees