文件名称:SVC
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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.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
SVC
...\Matlab辅助函数文件
...\..................\ClassResult.m
...\..................\SVMcgForClass.m
...\..................\gaSVMcgForClass.m
...\..................\psoSVMcgForClass.m
...\..................\scaleForSVM.m
...\libsvm-3.20工具箱
...\.................\COPYRIGHT
...\.................\FAQ.html
...\.................\Makefile
...\.................\Makefile.win
...\.................\README
...\.................\heart_scale
...\.................\java
...\.................\....\Makefile
...\.................\....\libsvm
...\.................\....\......\svm.java
...\.................\....\......\svm.m4
...\.................\....\......\svm_model.java
...\.................\....\......\svm_node.java
...\.................\....\......\svm_parameter.java
...\.................\....\......\svm_print_interface.java
...\.................\....\......\svm_problem.java
...\.................\....\libsvm.jar
...\.................\....\svm_predict.java
...\.................\....\svm_scale.java
...\.................\....\svm_toy.java
...\.................\....\svm_train.java
...\.................\....\test_applet.html
...\.................\matlab
...\.................\......\Makefile
...\.................\......\README
...\.................\......\libsvmread.c
...\.................\......\libsvmwrite.c
...\.................\......\make.m
...\.................\......\svm_model_matlab.c
...\.................\......\svm_model_matlab.h
...\.................\......\svmpredict.c
...\.................\......\svmtrain.c
...\.................\python
...\.................\......\Makefile
...\.................\......\README
...\.................\......\svm.py
...\.................\......\svmutil.py
...\.................\svm-predict.c
...\.................\svm-scale.c
...\.................\svm-toy
...\.................\.......\gtk
...\.................\.......\...\Makefile
...\.................\.......\...\callbacks.cpp
...\.................\.......\...\callbacks.h
...\.................\.......\...\interface.c
...\.................\.......\...\interface.h
...\.................\.......\...\main.c
...\.................\.......\...\svm-toy.glade
...\.................\.......\qt
...\.................\.......\..\Makefile
...\.................\.......\..\svm-toy.cpp
...\.................\.......\windows
...\.................\.......\.......\svm-toy.cpp
...\.................\svm-train.c
...\.................\svm.cpp
...\.................\svm.def
...\.................\svm.h
...\.................\tools
...\.................\.....\README
...\.................\.....\checkdata.py
...\.................\.....\easy.py
...\.................\.....\grid.py
...\.................\.....\subset.py
...\.................\windows
...\.................\.......\libsvm.dll
...\.................\.......\libsvmread.mexw64
...\.................\.......\libsvmwrite.mexw64
...\.................\.......\svm-predict.exe
...\.................\.......\svm-scale.exe
...\.................\.......\svm-toy.exe
...\.................\.......\svm-train.exe
...\.................\.......\svmpredict.mexw64
...\.................\.......\svmtrain.mexw64
...\分类模型源程序
...\..............\data.mat
...\..............\final_Classification_model.m
...\..............\initial_Classification_model.m
...\参数优化源程序
...\..............\GA_For_cg.m
...\..............\PSO_For_cg.m
...\..............\WangGe_For_cg.m
...\封装模型
...\........\SVC.m
...\数据文件
...\........\Data.xlsx
...\........\data.mat