Bayesian neural network for microarray data

被引：6

作者：

Liang, YL ^{[1
]}

George, EO ^{[1
]}

Kelemen, A ^{[1
]}

机构：

[1] Memphis State Univ, Dept Math Sci, Memphis, TN 38152 USA

来源：

PROCEEDING OF THE 2002 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-3 | 2002年

关键词：

D O I：

10.1109/IJCNN.2002.1005468

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose Bayesian Neural Networks (BNN) with structural learning for exploring microarray data in gene expressions. The approach employs representative data and regularization to capture correlation among gene expressions and Bayesian techniques to extract gene expression information from noisy data. The performance was verified with stratified cross-validation and multiple iterated runs.

引用

页码：193 / 197

页数：5

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