文件名称:GA_SVM
介绍说明－－下载内容均来自于网络，请自行研究使用
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。-For small sample case, SVM simulation results than the neural network is good, but the performance of SVM depends on its two training parameters, the algorithm is automatically selected GA parameters of SVM-2.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
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
......\osu_svm3.00\demo
......\osu_svm3.00
GA_SVM
......\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
......\osu_svm3.00\demo
......\osu_svm3.00
GA_SVM