A Study On Rough Set Based Data Mining Uncertainty

Missing or incomplete data are a major concern in data mining both because a substantial proportion of the data may be missing in real-world applications and because poor methods for incomplete data will bias the results of data mining. In addition, it is of great difficulty for data mining in an incomplete information system, which contains more uncertainty than a complete one does.This paper applies rough set theory-a mathematical tool for dealing with inexact, uncertain or vague knowledge-to handling incomplete data in data mining, so as to reduce the large gap between the available data and the machinery available to process the data.Firstly, The development the main body of a book is excavated first to the rough collection theory and data expounds , includes rough collection rationale , studies direction and studies a field; Uncertainty in the concept , characteristic , mission , classification , call for and data that the data excavates being excavated; Priority explains rough collection theory but the basis and rough collection excavating method's as the data apply to several kinds method in common use that the data excavates.Priority surrounds rough collection and method combines other each other and then on excavating a rationale in rough no complete collection theory information system data,have set forth rough collection- decision-making tree application in excavating in the data; Excavate method owing to rough collection and inheritance algorithm data; Rough collection neural networks algorithm application in excavating in the data.The at last has applied theory to practice to resolve the actual problem , has taken that colleges and universities student achievement analyses as example , has brought forward the scheme excavating solving that the technology middle applies to achievement analysis owing to rough collection theory data , indicated a data excavating a technology having the good effect in analysing the factor affecting colleges and universities student academic record, the technology a data is excavated applies to colleges and universities teaching each aspect , ought to be able to get large amount of the result having practical or immediate significance , come to improve education quality of teaching working out corresponding measure thereby.