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dd_tools安装条件以及svdd

发布时间:2021-11-22 12:15:46 所属栏目:教程 来源:互联网
导读:function W = svdd(a,fracrej,sigma) [alf,R2,Dx,J] = svdd_optrbf(sigma,+a,signlab,C); 只要就是用这两个函数,求出半径R2和alf。 工具包里边给的这个两个函数可能会涉及到一些画图啊之类的,然后一个调用一个,一出问题了就很麻烦,你可以看他的程序自己

function W = svdd(a,fracrej,sigma)
 
[alf,R2,Dx,J] = svdd_optrbf(sigma,+a,signlab,C);
 
只要就是用这两个函数,求出半径R2和alf。
 
工具包里边给的这个两个函数可能会涉及到一些画图啊之类的,然后一个调用一个,一出问题了就很麻烦,你可以看他的程序自己编,把一些不相干的去掉。
 
其他的会调用到欧氏距离、映射函数之类的,里边都有给了。
 
Data Description Matlab toolbox. (version 1.9.1)
 
This toolbox is an add-on to the PRTools toolbox. The toolbox contains algorithms to train, investigate, visualize and evaluate one-class classifiers (or data descriptions, novelty descriptors, outlier detectors). Some experience with the PRTools toolbox is recommended. This toolbox is developed as a research tool so no guarantees can be given.
 
 
- Requirements:
In order to make this toolbox work, you need:
0. A computer and some enthusiasm
1. Matlab with the - optimization toolbox (for svdd and lpdd)
                                - statistics toolbox (for randsph)
                        and - neural network toolbox (for autoenc_dd)
2. PRTools 4.0.0 or higher
3. This toolbox.
 
 
- Installation:
The installation of the toolbox is almost trivial. Unzip the file, store the contents in a directory (name it for instance DD_TOOLS) and add this directory to your matlab path.
 
 
- Information and example code:
For the most basic information, type help DD_TOOLS (use the directory name where the toolbox is stored). Some simple (and some not so simple!) one-class examples are given in dd_ex1 till dd_ex15. For more background information, please have a look at the pdf file included in the directory. Some examples of the operation of the procedures in the toolbox are given on the web-pages:
http://prlab.tudelft.nl/david-tax/dd_tools.html

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