International Journal of Computer Science and Security | |
Implementation of Back-Propagation Algorithm for Renal Datamining | |
P.Thrimurthy1  S.Purushothaman1  S Sai1  | |
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关键词: adaptation; adaptive learning; context; learning activity; learner model; learning automata; | |
DOI : | |
来源: Computer Science and Security | |
【 摘 要 】
The present medical era data mining place a important role for quick access of appropriate information. To achieve this full automation is required which means less human interference. Therefore automatic renal data mining with decision making algorithm is necessary. Renal failure contributes to major health problem. In this research work a distributed neural network has been applied to a data mining problem for classification of renal data to have for proper diagnosis of patient. A multi layer perceptron with back propagation algorithm has been used. The network was trained offline using 500 patterns each of 17 inputs. Using the weight obtained during training, fresh patterns were tested for accuracy of diagnosis.
【 授权许可】
Unknown
【 预 览 】
Files | Size | Format | View |
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RO201912040511437ZK.pdf | 224KB | download |