文件名称:libsvm-3.22
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [MacOS] [Matlab] [源码]
- 上传时间：
- 2016-12-28
- 文件大小：
- 820kb
- 下载次数：
- 1次
- 提 供 者：
- carl****
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
libsvm-3.22.rar LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include-libsvm-3.22.rar LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include-libsvm-3.22.rar LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification.
Since version 2.8, it implements an SMO-type algorithm proposed in this paper:
R.-E. Fan, P.-H. Chen, and C.-J. Lin. Working set selection using second order information for training SVM. Journal of Machine Learning Research 6, 1889-1918, 2005. You can also find a pseudo code there. (how to cite LIBSVM)
Our goal is to help users other fields to easily use SVM as a tool. LIBSVM provides a simple interface where users can easily link it with their own programs. Main features of LIBSVM include
(系统自动生成,下载前可以参看下载内容)
下载文件列表
libsvm-3.22\libsvm-3.22\COPYRIGHT
...........\...........\FAQ.html
...........\...........\heart_scale
...........\...........\java\libsvm\svm.java
...........\...........\....\......\svm.m4
...........\...........\....\......\svm_model.java
...........\...........\....\......\svm_node.java
...........\...........\....\......\svm_parameter.java
...........\...........\....\......\svm_print_interface.java
...........\...........\....\......\svm_problem.java
...........\...........\....\libsvm.jar
...........\...........\....\Makefile
...........\...........\....\svm_predict.java
...........\...........\....\svm_scale.java
...........\...........\....\svm_toy.java
...........\...........\....\svm_train.java
...........\...........\....\test_applet.html
...........\...........\Makefile
...........\...........\Makefile.win
...........\...........\matlab\libsvmread.c
...........\...........\......\libsvmread.mexw64
...........\...........\......\libsvmwrite.c
...........\...........\......\libsvmwrite.mexw64
...........\...........\......\make.m
...........\...........\......\Makefile
...........\...........\......\README
...........\...........\......\svmpredict.c
...........\...........\......\svmpredict.mexw64
...........\...........\......\svmtrain.c
...........\...........\......\svmtrain.mexw64
...........\...........\......\svm_model_matlab.c
...........\...........\......\svm_model_matlab.h
...........\...........\python\Makefile
...........\...........\......\README
...........\...........\......\svm.py
...........\...........\......\svmutil.py
...........\...........\README
...........\...........\svm-predict.c
...........\...........\svm-scale.c
...........\...........\....toy\gtk\callbacks.cpp
...........\...........\.......\...\callbacks.h
...........\...........\.......\...\interface.c
...........\...........\.......\...\interface.h
...........\...........\.......\...\main.c
...........\...........\.......\...\Makefile
...........\...........\.......\...\svm-toy.glade
...........\...........\.......\qt\Makefile
...........\...........\.......\..\svm-toy.cpp
...........\...........\.......\windows\svm-toy.cpp
...........\...........\svm-train.c
...........\...........\svm.cpp
...........\...........\svm.def
...........\...........\svm.h
...........\...........\tools\checkdata.py
...........\...........\.....\easy.py
...........\...........\.....\grid.py
...........\...........\.....\README
...........\...........\.....\subset.py
...........\...........\Untitled.m
...........\...........\windows\libsvm.dll
...........\...........\.......\libsvmread.mexw64
...........\...........\.......\libsvmwrite.mexw64
...........\...........\.......\svm-predict.exe
...........\...........\.......\svm-scale.exe
...........\...........\.......\svm-toy.exe
...........\...........\.......\svm-train.exe
...........\...........\.......\svmpredict.mexw64
...........\...........\.......\svmtrain.mexw64
...........\...........\.......\Untitled.m
...........\...........\java\libsvm
...........\...........\svm-toy\gtk
...........\...........\.......\qt
...........\...........\.......\windows
...........\...........\java
...........\...........\matlab
...........\...........\python
...........\...........\svm-toy
...........\...........\tools
...........\...........\windows
...........\libsvm-3.22
libsvm-3.22