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dd_tools安裝要求以及svdd

日期:2017/3/1 10:08:14   编辑:Linux編程

function W = svdd(a,fracrej,sigma)

[alf,R2,Dx,J] = svdd_optrbf(sigma,+a,signlab,C);

只要就是用這兩個函數,求出半徑R2和alf。

工具包裡邊給的這個兩個函數可能會涉及到一些畫圖啊之類的,然後一個調用一個,一出問題了就很麻煩,你可以看他的程序自己編,把一些不相干的去掉。

其他的會調用到歐氏距離、映射函數之類的,裡邊都有給了。

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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