Cluster ensemble for gene expression Microarray data

被引：0
|
作者：
de Souto, MCP [1 ]
Silva, SCM [1 ]
Bittencourtt, VG [1 ]
de Araujo, DSA [1 ]
机构：
[1] Univ Fed Rio Grande do Norte, Dept Informat & Appl Math, BR-59072970 Natal, RN, Brazil
来源：
PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), VOLS 1-5 | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Ensemble techniques have been successfully applied in the context of supervised learning to increase the accuracy and stability of classification. Recently, similar techniques have been proposed for clustering, algorithms. In this context, we analyze the potential of applying cluster ensemble techniques to gene expression microarray data. Our experimental results show that there is often a significant improvement in the results obtained with the use of ensemble when compared to those based on the clustering techniques used individually.
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页码：487 / 492
页数：6
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