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SVC

于 2016-11-27 发布 文件大小:635KB
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代码说明:

  建立LibSVM预测模型,基于网格算法、粒子群算法、遗传算法优化了模型参数,并由最终模型预测了给定切削参数下零件的粗糙度等级。(Establish LibSVM prediction model, grid-based algorithm, particle swarm optimization, genetic algorithm to optimize the parameters of the model, the final model prediction given by the cutting parameters of parts roughness class.)

文件列表:

SVC
...\libsvm-3.20工具箱
...\.................\htm" target=_blank>COPYRIGHT,1497,2014-11-15
...\.................\FAQ.html,78969,2014-11-15
...\.................\htm" target=_blank>heart_scale,27670,2014-11-15
...\.................\java
...\.................\....\libsvm
...\.................\....\......\svm.java,63803,2014-11-15
...\.................\....\......\svm.m4,63095,2014-11-15
...\.................\....\......\svm_model.java,868,2014-11-15
...\.................\....\......\svm_node.java,115,2014-11-15
...\.................\....\......\svm_parameter.java,1288,2014-11-15
...\.................\....\......\svm_print_interface.java,87,2014-11-15
...\.................\....\......\svm_problem.java,136,2014-11-15
...\.................\....\libsvm.jar,51917,2014-11-15
...\.................\....\Makefile,624,2014-11-15
...\.................\....\svm_predict.java,4950,2014-11-15
...\.................\....\svm_scale.java,8944,2014-11-15
...\.................\....\svm_toy.java,12269,2014-11-15
...\.................\....\svm_train.java,8355,2014-11-15
...\.................\....\test_applet.html,81,2014-11-15
...\.................\Makefile,732,2014-11-15
...\.................\Makefile.win,1084,2014-11-15
...\.................\matlab
...\.................\......\libsvmread.c,4063,2014-11-15
...\.................\......\libsvmwrite.c,2341,2014-11-15
...\.................\......\make.m,777,2014-11-15
...\.................\......\Makefile,1240,2014-11-15
...\.................\......\htm" target=_blank>README,9826,2014-11-15
...\.................\......\svmpredict.c,9823,2014-11-15
...\.................\......\svmtrain.c,11821,2014-11-15
...\.................\......\svm_model_matlab.c,8208,2014-11-15
...\.................\......\svm_model_matlab.h,201,2014-11-15
...\.................\python
...\.................\......\Makefile,32,2014-11-15
...\.................\......\htm" target=_blank>README,11908,2014-11-15
...\.................\......\svm.py,9605,2014-11-15
...\.................\......\svmutil.py,8695,2014-11-15
...\.................\htm" target=_blank>README,28544,2014-11-15
...\.................\svm-predict.c,5536,2014-11-15
...\.................\svm-scale.c,8504,2014-11-15
...\.................\svm-toy
...\.................\.......\gtk
...\.................\.......\...\callbacks.cpp,10308,2014-11-15
...\.................\.......\...\callbacks.h,1765,2014-11-15
...\.................\.......\...\interface.c,6457,2014-11-15
...\.................\.......\...\interface.h,203,2014-11-15
...\.................\.......\...\main.c,398,2014-11-15
...\.................\.......\...\Makefile,573,2014-11-15
...\.................\.......\...\svm-toy.glade,6402,2014-11-15
...\.................\.......\qt
...\.................\.......\..\Makefile,392,2014-11-15
...\.................\.......\..\svm-toy.cpp,9744,2014-11-15
...\.................\.......\windows
...\.................\.......\.......\svm-toy.cpp,11503,2014-11-15
...\.................\svm-train.c,8986,2014-11-15
...\.................\svm.cpp,64702,2014-11-15
...\.................\svm.def,477,2014-11-15
...\.................\svm.h,3382,2014-11-15
...\.................\tools
...\.................\.....\checkdata.py,2479,2014-11-15
...\.................\.....\easy.py,2699,2014-11-15
...\.................\.....\grid.py,15316,2014-11-15
...\.................\.....\htm" target=_blank>README,7033,2014-11-15
...\.................\.....\subset.py,3202,2014-11-15
...\.................\windows
...\.................\.......\libsvm.dll,160256,2014-11-15
...\.................\.......\libsvmread.mexw64,11264,2014-11-15
...\.................\.......\libsvmwrite.mexw64,10240,2014-11-15
...\.................\.......\svm-predict.exe,125952,2014-11-15
...\.................\.......\svm-scale.exe,81408,2014-11-15
...\.................\.......\svm-toy.exe,141312,2014-11-15
...\.................\.......\svm-train.exe,155648,2014-11-15
...\.................\.......\svmpredict.mexw64,25600,2014-11-15
...\.................\.......\svmtrain.mexw64,64000,2014-11-15
...\Matlab辅助函数文件
...\..................\ClassResult.m,2087,2015-07-10
...\..................\gaSVMcgForClass.m,3272,2015-07-10
...\..................\psoSVMcgForClass.m,5222,2015-07-10
...\..................\scaleForSVM.m,540,2015-07-10
...\..................\SVMcgForClass.m,2180,2015-07-10
...\分类模型源程序
...\..............\data.mat,489,2015-07-12
...\..............\final_Classification_model.m,4412,2015-07-10
...\..............\initial_Classification_model.m,2170,2015-07-09
...\参数优化源程序
...\..............\GA_For_cg.m,2302,2015-07-10
...\..............\PSO_For_cg.m,2100,2015-07-10
...\..............\WangGe_For_cg.m,2571,2015-07-10
...\封装模型
...\........\SVC.m,3714,2015-07-10
...\数据文件
...\........\data.mat,489,2015-07-10
...\........\Data.xlsx,11658,2015-07-07

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