在癌症分类中基于分层抽样的神经网络集成算法

在基因表达谱数据的分析中,针对有效合理地选择特征基因集的问题,本文将分层抽样技术引入特征基因选择,提高特征基因集的分类能力。以神经网络作为分量分类器,神经网络集成进行分类预测。并在结肠癌数据集上进行实验,实验结果表明该方法能有效地降低特征基因集选择的复杂性,提高对于未知样本的分类预测效果。

A neural network ensemble method based on the stratified sampling in tumor classification

With introducing the stratified sampling into the character gene's selection for the problem of choosing gene as charater gene group effectively and rationaly in the analysis of the expression profiles,a feature selection method based on the stratified sampling was proposed for improving the classification ability of character gene group. And a network ensemble which neural networks was taken as the individual classification is employed to classify the samples. In the end,this method was experimentize in th...