用GA自动选择SVM的两个参数我要分享

Using GA to select two parameters of SVM automatically

小样本训练 GASVM ga-neural-network SVM--快速 GA-SVM

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文件大小: 1635KB

代码分类: 仿真计算

开发平台: matlab

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代码描述

中文说明:

对于小样本而言,SVM的仿真效果要比神经网络好,但是SVM的性能依赖于它的两个训练参数,本算法是用GA自动选择SVM的两个参数。




























English Description:

For small samples, the simulation effect of SVM is better than that of neural network, but the performance of SVM depends on its two training parameters. This algorithm uses GA to automatically select two parameters of SVM.




























代码预览

GA_SVM

......\ALLdataTest.m

......\ALLdataTrain.m

......\mainGA7.m

......\osu_svm3.00

......\...........\cmap.mat

......\...........\Contents.m

......\...........\demo

......\...........\....\c_clademo.m

......\...........\....\c_lindemo.m

......\...........\....\c_poldemo.m

......\...........\....\c_rbfdemo.m

......\...........\....\c_svcdemo.m

......\...........\....\DemoData_class.mat

......\...........\....\DemoData_test.mat

......\...........\....\DemoData_train.mat

......\...........\....\one_rbfdemo.m

......\...........\....\osusvmdemo.m

......\...........\....\SVMClassifier.mat

......\...........\....\u_clademo.m

......\...........\....\u_lindemo.m

......\...........\....\u_poldemo.m

......\...........\....\u_rbfdemo.m

......\...........\....\u_svcdemo.m

......\...........\demos.m

......\...........\LinearSVC.m

......\...........\mexSVMClass.dll

......\...........\mexSVMClass.m

......\...........\mexSVMClass.mexglx

......\...........\mexSVMClass.mexhp7

......\...........\mexSVMClass.mexsol

......\...........\mexSVMTrain.dll

......\...........\mexSVMTrain.m

......\...........\mexSVMTrain.mexglx

......\...........\mexSVMTrain.mexhp7

......\...........\mexSVMTrain.mexsol

......\...........\Normalize.m

......\...........\one_RbfSVC.m

......\...........\PolySVC.m

......\...........\RbfSVC.m

......\...........\Scale.m

......\...........\SVMClass.m

......\...........\SVMPlot.m

......\...........\SVMPlot2.m

......\...........\SVMTest.m

......\...........\SVMTrain.m

......\...........\u_LinearSVC.m

......\...........\u_PolySVC.m

......\...........\u_RbfSVC.m

......\Readme_of_GASVM.txt

......\selectGA7.m

......\svmc7.m