The Study of the Application to Data Mining with Rough Sets Theory

The rough sets theory can effectively express inexact or uncertain knowledge ,and is good at acquiring the knowledge from data. It can reason from uncertain and incomplete experience or knowledge.Therefore ,the application of the rough sets theory is more and more welcome in data mining (i.e.knowledge discovery). Taking the survey sample database for purcehase intentions of car users as a example,The paper detailedly introduces a way to apply the rough sets theory in data mining as follow:firstly,according to acquired original sample information , make knowledge categories for car users and their key attentions for purehase intentions ; secondly, construct a original decision table determining their key attentions for purehase intentions as condition attributes, and car users as decision attribute; thirdly, according to Adding method relative to the knowledge core and value core of attributes, find respectively its relative knowledge reduction sets and value reduction sets; finally, from simplified decision tables for the minimum relative knowledge reduction sets, extract decision rules. Compared with other data mining , besides dealing with data the way does not require any prior information,and can acquire useful knowledge only by analyzing ,judging and mining original sample information.