基于聚类算法的选择性神经网络集成在大脑胶质瘤诊断中的应用

R73; A clustering algorithm based selective neural networks ensemble (CLUSEN) is proposed to predict the degree of malignancy in brain glioma.Since the degree prediction of malignancy is critical before brain surgery, many learning methods are used like rule induction algorithm, single neural networ...

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Bibliographic Details
Published in上海大学学报（英文版） Vol. 10; no. 3; pp. 244 - 246
Main Authors 刘天羽, 李国正, 吴耿锋
Format Journal Article
LanguageChinese
Published 上海大学 2006
Subjects
ensemble learning
clustering algorithm
brain glioma
neural networks
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ISSN1007-6417

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Summary:R73; A clustering algorithm based selective neural networks ensemble (CLUSEN) is proposed to predict the degree of malignancy in brain glioma.Since the degree prediction of malignancy is critical before brain surgery, many learning methods are used like rule induction algorithm, single neural networks, support vector machines, etc.Ensemble learning methods can improve the generalization of single learning machine, and are becoming popular in the machine learning and medical data processing communities.The procedure of CLUSEN can efficiently remove redundancy learning individuals and help improve the diversity of ensemble methods.CLUSEN is used to predict the degree of malignancy in brain glioma.Experimental results on a set of brain glioma data show that, compared to support vector machines, rule induction and single neural networks, the classification accuracy of CLUSEN is higher.
ISSN:1007-6417