SVM-matlab

所属分类:matlab编程
开发工具:matlab
文件大小:3846KB
下载次数:45
上传日期:2013-11-17 22:00:44
上 传 者dongshanyiqi
说明:  经典SVM算法matlab程序,用于多种利用MATLAB对数据进行SVM仿真的实验。
(Classical SVM algorithm matlab program for a variety of SVM data using MATLAB simulation experiments.)

文件列表:
经典SVM算法matlab程序\svm\binomial.m (371, 1997-09-19)
经典SVM算法matlab程序\svm\centrefig.m (144, 1998-05-01)
经典SVM算法matlab程序\svm\cmap.mat (1728, 1997-08-13)
经典SVM算法matlab程序\svm\Contents.m (1105, 1998-08-07)
经典SVM算法matlab程序\svm\Examples\Classification\iris1v23.mat (2696, 1997-09-28)
经典SVM算法matlab程序\svm\Examples\Classification\iris2v13.mat (2696, 1997-09-28)
经典SVM算法matlab程序\svm\Examples\Classification\iris3v12.mat (2696, 1997-09-28)
经典SVM算法matlab程序\svm\Examples\Classification\linsep.mat (672, 1997-11-06)
经典SVM算法matlab程序\svm\Examples\Classification\nlinsep.mat (712, 1997-11-06)
经典SVM算法matlab程序\svm\Examples\Regression\example.mat (744, 1997-11-07)
经典SVM算法matlab程序\svm\Examples\Regression\sinc.mat (1056, 1997-08-20)
经典SVM算法matlab程序\svm\Examples\Regression\titanium.mat (1096, 1997-09-27)
经典SVM算法matlab程序\svm\newsvm.zip (76534, 2001-10-26)
经典SVM算法matlab程序\svm\nobias.m (457, 1998-08-06)
经典SVM算法matlab程序\svm\Optimiser\Makefile (27, 2001-10-11)
经典SVM算法matlab程序\svm\Optimiser\pr_loqo.c (16731, 2001-10-11)
经典SVM算法matlab程序\svm\Optimiser\pr_loqo.h (2388, 2001-10-11)
经典SVM算法matlab程序\svm\Optimiser\qp.c (7245, 2001-10-11)
经典SVM算法matlab程序\svm\Optimiser\qp.dll (49152, 2001-10-26)
经典SVM算法matlab程序\svm\qp.dll (49152, 2001-10-26)
经典SVM算法matlab程序\svm\softmargin.m (312, 1998-04-21)
经典SVM算法matlab程序\svm\svc.m (2687, 1998-08-21)
经典SVM算法matlab程序\svm\svcerror.m (837, 1998-08-21)
经典SVM算法matlab程序\svm\svcinfo.m (1228, 1998-03-10)
经典SVM算法matlab程序\svm\svcoutput.m (973, 1998-04-21)
经典SVM算法matlab程序\svm\svcplot.m (3109, 2001-10-12)
经典SVM算法matlab程序\svm\svdatanorm.m (1299, 1998-06-23)
经典SVM算法matlab程序\svm\svkernel.m (2608, 2001-10-11)
经典SVM算法matlab程序\svm\svr.m (3982, 1998-08-21)
经典SVM算法matlab程序\svm\svrerror.m (1203, 1998-08-21)
经典SVM算法matlab程序\svm\svroutput.m (711, 1998-04-15)
经典SVM算法matlab程序\svm\svrplot.m (1823, 1998-02-13)
经典SVM算法matlab程序\svm\svtol.m (401, 1998-08-21)
经典SVM算法matlab程序\svm\uiclass.m (5386, 1997-11-18)
经典SVM算法matlab程序\svm\uiclass.mat (12592, 1997-11-18)
经典SVM算法matlab程序\svm\uiregress.m (5627, 1997-09-27)
经典SVM算法matlab程序\svm\uiregress.mat (11640, 1998-10-12)
经典SVM算法matlab程序\SVM_luzhenbo\Classification_stprtool.m (2351, 2007-03-15)
经典SVM算法matlab程序\SVM_luzhenbo\Classification_SVM_SteveGunn.m (1542, 2007-03-15)
... ...

% Statistical Pattern Recognition Toolbox, Vojtech Franc, Vaclav Hlavac % (c) Czech Technical University Prague, http://cmp.felk.cvut.cz % Written Vojtech Franc (diploma thesis) 26.02.2000 % Modifications % 24. 6.00 V. Hlavac Text polished. ===================================================================== 0. Contents =========== 0. Contents 1. Introduction 2. Requirements 3. Installation 4. Quick Start 5. How to start ? 1. Introduction ==================== This toolbox implements a selection of major statistical pattern methods as described in the monograph Schlesinger M.I., Hlavac V. Ten lectures from the statistical and syntactic pattern recognition (in Czech), Czech Technical University Publishing House, September 1999 (further referred as SH10). English version should appear in Kluwer Academic Publishers. The basic idea of the toolbox was sketched by M.I. Schlesinger and V. Hlavac in June 1999. The design of the toolbox and implementation is by V. Franc who did it as his diploma work at the Czech Technical University Praha, Czech Republic (defended February 2000). V. Franc continues developing the toolbox as he is the PhD student of the Center for Machine Perception, cf. http://cmp.felk.cvut.cz The aim of the toolbox is to (a) Provide tools for experimenting with various statistical pattern recognition methods. (b) Aid the reader of the above mentioned rather theoretical book the practical skills. (c) Provides the teachers of pattern recognition courses the tool they can use with their students in laboratory exercises. This software can be used freely for academic, non-profit purposes. If you intend to use it for commercial development, please, contact us. 2. Requirements ================ - Matlab, version 5.2 and higher. - Optimization Toolbox (MathWorks). - Statistic Toolbox (MathWorks). 3. Installation ================ The "stprtool" directory is a root directory of the statistical pattern recognition toolbox. - Create a directory of your choice and copy the toolbox there. - The path to toolbox directories has to be set before using the toolbox. This can be done automatically each time Matlab is initiated or manually. We describe the first option here and the second is described in the next section. - Windows: Copy file "\stprtool\setpath.m" to your "..\matlab\toolbox\local\" directory. Linux: Copy file "\stprtool\setpath.m" to "\your_home\matlab\" - Add line setpath('path'); to your "startup.m" file. The argument path is the name of the toolbox root directory. For example, if the toolbox is located in your root directory on disk c then use setpath('c:\stprtool'); note: The "startup.m" file is located in Windows: "..\matlab\toolbox\local\" directory, Linux: "\your_home\matlab\" directory if it does not exist you have to create it. 4. Start toolbox with manual set of the path =============== - Run Matlab - Change directory to the toolbox root. Use Matlab command "cd", for example cd c:\stprtool - Type setpath 5. How to start ? ==================== After the toolbox is installed, run Matlab and you can start using the toolbox. At first, try to type help stprtool and you will get a list of available demo programs. You can also read html-documentation in "/stprtool/doc/html/". If you have any comments or suggestions then send me an email at xfrancv@cmp.felk.cvut.cz

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