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The Study On The Neural Network Classification And The Extracting Rule Technology

Posted on:2006-12-27Degree:MasterType:Thesis
Country:ChinaCandidate:T Z HeFull Text:PDF
GTID:2178360182461477Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
Data classification is the important function of the Data mining and Neural Network which has anti-noise and strong becomes a Data mining tool and especially in the Data classification. But, Neural Network is a black-box for the user and for its knowledge implies the weight of the conjunction the user can not comprehend the knowledge. In order to resolve this problem, in this paper we build a Data classification model based on the Neural Network. This Data classification can make the knowledge understanding by using the data process, training Neural Network and extracting rale. In this Data classification, first, we generalize the continue data and encode the nominal data. Second, we acquire the knowledge by training the Neural Network. Last, we extract the rule from the Neural Network by the Function method. In this method the Neural Network is looked as a black-box and we input a random input-data and then the Network can create the output. A instance is consist of the random input-data and output. We reduce the instances and can acquire the rules by using the Rough set.
Keywords/Search Tags:Data Mining, Neural Network, rule extracting, Rough Set
PDF Full Text Request
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