SVM
所属分类:matlab编程
开发工具:matlab
文件大小:10974KB
下载次数:62
上传日期:2015-12-14 21:31:39
上 传 者:
小刘同学
说明: SVM多分类算法的一些程序,有很多种类型,包括经典的四种工具箱,还有代价敏感支持向量机,超球面支持向量机等
(Some programs about SVM multi-classification algorithm, there are many types, including the classic four toolbox, as well as the price-sensitive support vector machine, hypersphere support vector machine)
文件列表:
SVM\SVM入门.doc (398336, 2015-07-13)
SVM\最小二乘支持向量机.rar (2144036, 2015-07-13)
SVM\SVM多项分类.doc (82432, 2015-07-13)
SVM\SVM算法matlab程序.rar (4766972, 2015-07-13)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Optimiser\Makefile (27, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Optimiser\pr_loqo.c (16731, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Optimiser\pr_loqo.h (2388, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Optimiser\qp.c (7245, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Optimiser\qp.dll (49152, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Classification\iris1v23.mat (2696, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Classification\iris2v13.mat (2696, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Classification\iris3v12.mat (2696, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Classification\linsep.mat (672, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Classification\nlinsep.mat (712, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Regression\example.mat (744, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Regression\sinc.mat (1056, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Examples\Regression\titanium.mat (1096, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\binomial.m (371, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\centrefig.m (144, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\cmap.mat (1728, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\Contents.m (1105, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\newsvm.zip (76534, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\nobias.m (457, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\qp.dll (49152, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\softmargin.m (312, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svc.m (2687, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svcerror.m (837, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svcinfo.m (1228, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svcoutput.m (973, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svcplot.m (3109, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svdatanorm.m (1299, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svkernel.m (2608, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svr.m (3982, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svrerror.m (1203, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svroutput.m (711, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svrplot.m (1823, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\svtol.m (401, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\uiclass.m (5386, 2012-06-25)
SVM\SVM算法matlab程序\经典SVM算法matlab程序\svm\uiclass.mat (12592, 2012-06-25)
... ...
% 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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