libsvm-3.1-[FarutoUltimate3.1Mcode]
所属分类：人工智能/神经网络/深度学习
开发工具：matlab
文件大小：1452KB
下载次数：26
上传日期：2013-12-20 11:00:15
上 传 者：
iuujh
说明： LIBSVM的工具包，里边含有已经编译过的make，64位.32位一般都可以直接使用，的安装vc。这个工具包添加ClassResult.m函数，方便给出各种分类准确率，以及给出判别函数的权值w、偏置b、支持向量在原始训练集中的位置索引以及alpha系数。
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翻译
LIBSVM toolkit has been compiled containing inside make, 64 位 .32 bit can generally be used directly install vc. Right this kit to add ClassResult.m function to facilitate a variety of classification accuracy is given, and given the value of the discriminant function w, bias b, support vector in the original training set position index and alpha coefficients.
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文件列表:
libsvm-3.1-[FarutoUltimate3.1Mcode]\COPYRIGHT (1497, 2011-03-26)
libsvm-3.1-[FarutoUltimate3.1Mcode]\FAQ.html (68901, 2011-03-26)
libsvm-3.1-[FarutoUltimate3.1Mcode]\heart_scale (27670, 2003-07-12)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm.java (61931, 2011-03-26)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm.m4 (61280, 2010-11-05)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_model.java (734, 2010-09-12)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_node.java (115, 2003-10-11)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_parameter.java (1288, 2006-03-03)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_print_interface.java (87, 2009-02-18)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm\svm_problem.java (136, 2003-10-11)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\libsvm.jar (49854, 2011-03-26)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\Makefile (624, 2009-02-18)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_predict.java (4267, 2009-03-18)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_scale.java (8944, 2009-02-20)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_toy.java (11483, 2010-12-13)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\svm_train.java (8268, 2010-01-27)
libsvm-3.1-[FarutoUltimate3.1Mcode]\java\test_applet.html (81, 2003-07-12)
libsvm-3.1-[FarutoUltimate3.1Mcode]\Makefile (528, 2010-09-12)
libsvm-3.1-[FarutoUltimate3.1Mcode]\Makefile.win (1087, 2010-09-12)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\feature1.mat (110747, 2013-11-24)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\feature2.mat (48587, 2013-11-24)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\feature_labels.mat (196, 2013-11-23)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\heart_scale.mat (28904, 2005-03-22)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\Libsvm.asv (3856, 2013-11-26)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\Libsvm.m (3903, 2013-11-26)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmread.c (3988, 2011-02-24)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmread.mexw32 (20480, 2011-06-08)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmread.mexw64 (10752, 2013-11-23)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmwrite.c (2123, 2011-02-24)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmwrite.mexw32 (20480, 2011-06-08)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\libsvmwrite.mexw64 (9216, 2013-11-23)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\make.m (396, 2011-02-24)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\Makefile (1481, 2011-02-24)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\svm.obj (139871, 2013-11-23)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\svmpredict.c (9063, 2011-03-08)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\svmpredict.mexw32 (24576, 2011-06-08)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\svmpredict.mexw64 (23040, 2013-11-23)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\svmtrain.c (11355, 2011-06-08)
libsvm-3.1-[FarutoUltimate3.1Mcode]\matlab\svmtrain.c.bak (11343, 2011-03-08)
... ...
SVM faruto version
by faruto
Email:farutoliyang@gmail.com
2009.11.05
==================================
Content:
scaleForSVM:归一化
函数接口:
[train_scale,test_scale,ps] = scaleForSVM(train_data,test_data,ymin,ymax)
====================================
pcaForSVM:pca降维预处理
函数接口:
[train_pca,test_pca] = pcaForSVM(train,test,threshold)
====================================
fasticaForSVM:ica降维预处理
函数接口:
[train_ica,test_ica] = fasticaForSVM(train,test)
====================================
SVMcgForClass:分类问题参数寻找[grid search based on CV]
函数接口:
[bestacc,bestc,bestg] = SVMcgForClass(train_label,train,cmin,cmax,gmin,gmax,v,cstep,gstep,accstep)
SVMcgForRegress:回归问题参数寻优[grid search based on CV]
函数接口:
[mse,bestc,bestg] = SVMcgForRegress(train_label,train,cmin,cmax,gmin,gmax,v,cstep,gstep,msestep)
======================================
psoSVMcgForClass:分类问题参数寻优[pso based on CV]
函数接口:
[bestCVaccuracy,bestc,bestg,pso_option] = psoSVMcgForClass(train_label,train,pso_option)
psoSVMcgForRegress:回归问题参数寻优[pso based on CV]
函数接口:
[bestCVmse,bestc,bestg,pso_option] = psoSVMcgForRegress(train_label,train,pso_option)
=======================================
gaSVMcgForClass:分类问题参数寻优[ga based on CV]
函数接口:
[bestCVaccuracy,bestc,bestg,ga_option] = gaSVMcgForClass(train_label,train,ga_option)
gaSVMcgForRegress:回归问题参数寻优[ga based on CV]
函数接口:
[bestCVmse,bestc,bestg,ga_option] = gaSVMcgForRegress(train_label,train,ga_option)
======================================
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