SVM_SteveGunn

所属分类:图形图像处理
开发工具:matlab
文件大小:75KB
下载次数:83
上传日期:2011-12-07 15:12:34
上 传 者dingwei212
说明:  SVM分类器,是一种比较经典的分类算法,常用作图像识别分类中的分类器,这是作者改进过的一种SVM分类算法。
(svm satisfaction)

文件列表:
SVM_SteveGunn\binomial.m (371, 1997-09-19)
SVM_SteveGunn\centrefig.m (144, 1998-05-01)
SVM_SteveGunn\cmap.mat (1728, 1997-08-13)
SVM_SteveGunn\Contents.m (1118, 2006-03-23)
SVM_SteveGunn\Examples\Classification\iris1v23.mat (2696, 1997-09-28)
SVM_SteveGunn\Examples\Classification\iris2v13.mat (2696, 1997-09-28)
SVM_SteveGunn\Examples\Classification\iris3v12.mat (2696, 1997-09-28)
SVM_SteveGunn\Examples\Classification\linsep.mat (672, 1997-11-06)
SVM_SteveGunn\Examples\Classification\nlinsep.mat (712, 1997-11-06)
SVM_SteveGunn\Examples\Regression\example.mat (744, 1997-11-07)
SVM_SteveGunn\Examples\Regression\sinc.mat (1056, 1997-08-20)
SVM_SteveGunn\Examples\Regression\titanium.mat (1096, 1997-09-27)
SVM_SteveGunn\nobias.m (457, 1998-08-06)
SVM_SteveGunn\Optimiser\Makefile (27, 2001-10-11)
SVM_SteveGunn\Optimiser\pr_loqo.c (16731, 2001-10-11)
SVM_SteveGunn\Optimiser\pr_loqo.h (2388, 2001-10-11)
SVM_SteveGunn\Optimiser\qp.c (7245, 2001-10-11)
SVM_SteveGunn\Optimiser\qp.dll (49152, 2001-10-26)
SVM_SteveGunn\qp.dll (49152, 2001-10-26)
SVM_SteveGunn\softmargin.m (312, 1998-04-21)
SVM_SteveGunn\svc.m (2687, 2005-04-14)
SVM_SteveGunn\svcerror.m (837, 1998-08-21)
SVM_SteveGunn\svcinfo.m (1228, 1998-03-10)
SVM_SteveGunn\svcoutput.m (973, 1998-04-21)
SVM_SteveGunn\svcplot.m (3109, 2001-10-12)
SVM_SteveGunn\svdatanorm.m (1299, 1998-06-23)
SVM_SteveGunn\svkernel.m (2608, 2001-10-11)
SVM_SteveGunn\svr.asv (3861, 2005-04-14)
SVM_SteveGunn\svr.m (3982, 1998-08-21)
SVM_SteveGunn\svrerror.m (1203, 1998-08-21)
SVM_SteveGunn\svroutput.m (711, 1998-04-15)
SVM_SteveGunn\svrplot.m (1823, 1998-02-13)
SVM_SteveGunn\svtol.m (401, 1998-08-21)
SVM_SteveGunn\uiclass.m (5386, 1997-11-18)
SVM_SteveGunn\uiclass.mat (12592, 1997-11-18)
SVM_SteveGunn\uiregress.m (5627, 1997-09-27)
SVM_SteveGunn\uiregress.mat (11640, 1998-10-12)
SVM_SteveGunn\Examples\Classification (0, 2010-01-08)
... ...

Matlab Support Vector Machine Toolbox ------------------------------------- Author: Steve Gunn This toolbox was designed as a teaching aid, which matlab is particularly good for since source code is relatively legible and simple to modify. However, it is still reasonably fast if used with the supplied optimiser. However, if you really want to speed things up you should consider compiling the matrix composition routine for H into a mex function. Then again if you really want to speed things up you probably shouldn't be using matlab anyway... Get hold of a dedicated C program once you understand the algorithm. Enjoy! Version Info ------------ Version: 2.1, 12/10/2001 - interior point QP optimiser added Version: 2.0, 01/08/19*** - Bug Fixes Version: 1.0, 10/02/19*** - Initial release Licence ------- The Support Vector Machine Toolbox is ONLY available for academic purposes. It is not available for industrial or commercial applications of any kind without explicit arrangement with the author. The software must not be posted on any WWW or ftp sites or distributed in any other way without prior permission of the author. The author disclaims all warranties with regard to this software, including all implied warranties of merchantability and fitness. In no event shall the authors be liable for any special, indirect or consequential damages or any damages whatsoever resulting from loss of use, data or profits, whether in an action of contract, negligence or other tortious action, arising out of or in connection with the use or performance of this software. Permission to sell this software is not granted. Installation ------------ The distribution now comes in a zip file (partly due to some problems people were having trying to open tar files with winzip). Unzip the toolbox under the matlab toolbox directory and add ......./matlab/toolbox/svm to the matlab path. If you are running under a windows OS you should be ready to go. On an alternative OS you will need to build the optimiser. NOTE: The matlab optimisation toolbox also currently contains a qp program, although it says that it will be replaced by a quadprog in the future. Make sure that the svm toolbox path comes before at the front of the matlab path, and it will then use the routine supplied with the svm toolbox which should be more efficient. Optimiser --------- Go into the optimiser directory and type, mex -v qp.c pr_loqo.c mv qp.mex??? .. which will build the optimiser for your OS, where the extension .mex??? will vary depending upon your OS. Move this file up one directory or add the optimiser directory to the path as well

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