MATLAB用于支持向量机-svm_v251.rar
MATLAB用于支持向量机-svm_v251.rar
MATLAB用于支持向量机
Support Vector Machine toolbox for Matlab
Version 2.51, January 2002
Contents.m contains a brief description of all parts of this toolbox.
Main features are:
- Except for the QP solver, all parts are written in plain Matlab. This
guarantees for easy modification. Special kinds of kernels that require
much computation (such as the Fisher kernel, which is based on a model of
the data) can easily be incorporated.
- Extension to multi-class problems via error correcting output codes is
included.
- Unless many other SVM toolboxes, this one can handle SVMs with 1norm
or 2norm of the slack variables.
- For both cases, a decomposition algorithm is implemented for the training
routine, together with efficient working set selection strategies.
The training algorithm uses many of the ideas proposed by Thorsten
Joachims for his SVMlight. It thus should exhibit a scaling behaviour that
is comparable to SVMlight.
This toolbox optionally makes use of a Matlab wrapper for an interior point
code in LOQO style .
To compile the wrapper, run
mex loqo.c pr_loqo.c
Make sure you have turned on the compiler optimizations in mexopts.sh
The LOQO code can be retrieved from
http://www.kernel-machines.org/code/prloqo.tar.gz
The wrapper comes directly from Steve Gunn.
Copyright Anton Schwaighofer
mailto:anton.schwaighofer@gmx.net
This program is released unter the GNU General Public License.
See License.txt for details.
Changes in version 2.51:
- fixed bug in SVMTRAIN that prevented correct initialisation with
NET.recompute==Inf
Changes in version 2.5:
- Handling of multi-class problems with ECOC
- NET.recompute is set to Inf by default, thus all training is done
incrementally by default.
- Handling the case of all training examples being -1 or 1 correctly
Changes in version 2.4:
- Better selection of the initial working set
- Added workaround for a Matlab quadprog bug with badly conditioned
matrices
- There is now a new kernel function 'rbffull' where a full matrix
C may be put into an RBF kernel:
K = exp'*C*)
Changes in version 2.3:
- slightly more compact debug output
Changes in version 2.2:
- New default values for parameter qpsize that make the whole toolbox
*much* faster
- Workaround for a Matlab bug with sparse matrices
- Changed the definition of the RBF-Kernel: from |x-y|^2/
to |x-y|^2/. This means that all parameter settings for old
versions need to be updated!
- A few minor things I can't remember
Changes in version 2.1:
Fixed a nasty bug at the KKT check
Changes in version 2.0:
All relevant routines have been updated to allow the use of a SVM with
2norm of the slack variables .
MATLAB用于支持向量机
Support Vector Machine toolbox for Matlab
Version 2.51, January 2002
Contents.m contains a brief description of all parts of this toolbox.
Main features are:
- Except for the QP solver, all parts are written in plain Matlab. This
guarantees for easy modification. Special kinds of kernels that require
much computation (such as the Fisher kernel, which is based on a model of
the data) can easily be incorporated.
- Extension to multi-class problems via error correcting output codes is
included.
- Unless many other SVM toolboxes, this one can handle SVMs with 1norm
or 2norm of the slack variables.
- For both cases, a decomposition algorithm is implemented for the training
routine, together with efficient working set selection strategies.
The training algorithm uses many of the ideas proposed by Thorsten
Joachims for his SVMlight. It thus should exhibit a scaling behaviour that
is comparable to SVMlight.
This toolbox optionally makes use of a Matlab wrapper for an interior point
code in LOQO style .
To compile the wrapper, run
mex loqo.c pr_loqo.c
Make sure you have turned on the compiler optimizations in mexopts.sh
The LOQO code can be retrieved from
http://www.kernel-machines.org/code/prloqo.tar.gz
The wrapper comes directly from Steve Gunn.
Copyright Anton Schwaighofer
mailto:anton.schwaighofer@gmx.net
This program is released unter the GNU General Public License.
See License.txt for details.
Changes in version 2.51:
- fixed bug in SVMTRAIN that prevented correct initialisation with
NET.recompute==Inf
Changes in version 2.5:
- Handling of multi-class problems with ECOC
- NET.recompute is set to Inf by default, thus all training is done
incrementally by default.
- Handling the case of all training examples being -1 or 1 correctly
Changes in version 2.4:
- Better selection of the initial working set
- Added workaround for a Matlab quadprog bug with badly conditioned
matrices
- There is now a new kernel function 'rbffull' where a full matrix
C may be put into an RBF kernel:
K = exp'*C*)
Changes in version 2.3:
- slightly more compact debug output
Changes in version 2.2:
- New default values for parameter qpsize that make the whole toolbox
*much* faster
- Workaround for a Matlab bug with sparse matrices
- Changed the definition of the RBF-Kernel: from |x-y|^2/
to |x-y|^2/. This means that all parameter settings for old
versions need to be updated!
- A few minor things I can't remember
Changes in version 2.1:
Fixed a nasty bug at the KKT check
Changes in version 2.0:
All relevant routines have been updated to allow the use of a SVM with
2norm of the slack variables .
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资源详情
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本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明