Prediction of Neural Tube Defect Using Support Vector Machine

被引：0
|
作者：
JIN-FENG WANG~(#
Institute for Sustainable Water
ΔCity University of Hong Kong
* Institute of Population Science
机构：
来源：
Biomedical and Environmental Sciences | 2010年 / 23卷 / 03期
关键词：
NTD; Prediction; Small sample; SVM;
D O I：
暂无
中图分类号：
R748 [儿童神经病];
学科分类号：
1002 ;
摘要：
Objective To predict neural tube birth defect(NTD) using support vector machine(SVM).Method The dataset in the pilot area was divided into non overlaid training set and testing set.SVM was trained using the training set and the trained SVM was then used to predict the classification of NTD.Result NTD rate was predicted at village level in the pilot area. The accuracy of the prediction was 71.50%for the training dataset and 68.57%for the test dataset respectively.Conclusion Results from this study have shown that SVM is applicable to the prediction of NTD.
引用
收藏
页码：167 / 172
页数：6
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