如何进行交叉验证SVM分类器 [英] How to do cross validation SVM classifier
问题描述
我想通过将SVM分类器应用于大小为1089 * 43093的数据矩阵S来执行解码，并且基于11倍交叉计算标签的预测精度，表示为r验证分类程序.11倍交叉验证基于数据矩阵S，该数据矩阵分为训练和测试数据集以进行分类.具体地，该交叉验证仅用于计算预测精度r. 有人可以给我一些建议吗?非常感谢！
I want to perform a decoding by applying an SVM classifier to a data matirx S, the size of which is 1089*43093,and the prediction accuracy of the labels, denoted as r, is calculated based on a 11-fold cross-validation classification procedure.The 11 fold cross-validation is based on the data matrix S, which is separated into the training and testing data sets for classification. Specifically, this cross-validation is only for calculating the prediction accuracy r. Can anyone give me some suggestion to do this? Thanks a lot!
推荐答案
To carry out SVM classification, use libsvm.
一个好的入门教程是: https://sites.google.com/site /kittipat/libsvm_matlab
A good tutorial to start would be: https://sites.google.com/site/kittipat/libsvm_matlab
Matlab代码以供交叉验证参考
Matlab code for reference on cross validation:
在MATLAB上安装LibSVM: http://www.youtube.com/watch? v = Wz_4h_bH7-c
Installing LibSVM on MATLAB: http://www.youtube.com/watch?v=Wz_4h_bH7-c
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