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You can find an example for classifying a data using Matlab in the following link
 
You can find an example for classifying a data using Matlab in the following link
+
 
  http://www.igi.tugraz.at/lehre/EW/tutorials/nnt_intro/index.html
+
http://www.igi.tugraz.at/lehre/EW/tutorials/nnt_intro/index.html
  
  
 
In the file 'nnt_intro_classification.m' it creates NN with 5 hidden units, 3 output units, logsig activation function for each layer. You need to change the configuration to improve the performance and refer to the pdf file in the downloaded zipped file.
 
In the file 'nnt_intro_classification.m' it creates NN with 5 hidden units, 3 output units, logsig activation function for each layer. You need to change the configuration to improve the performance and refer to the pdf file in the downloaded zipped file.
  
[[Category:Matlab Neural Network Toolbox for Classification]]
+
 
  
  
 
You can download SVM library in the following link
 
You can download SVM library in the following link
  http://www.csie.ntu.edu.tw/~cjlin/libsvm/
+
http://www.csie.ntu.edu.tw/~cjlin/libsvm/
  
 
You need to download the following file from the link
 
You need to download the following file from the link
    MATLAB A simple MATLAB interface LIBSVM authors at National Taiwan University.  2.85  Zip
+
MATLAB A simple MATLAB interface LIBSVM authors at National Taiwan University.  2.85  Zip
  
 
When you run 'make_win.m' in the Matlab command prompt it will generate dll files which are callable in Matlab.
 
When you run 'make_win.m' in the Matlab command prompt it will generate dll files which are callable in Matlab.
 
Before running 'make_win.m' you need to setup the default compiler used by mex by running 'mex -setup'
 
Before running 'make_win.m' you need to setup the default compiler used by mex by running 'mex -setup'
  
 +
Datasets at UCI Irwin Machine Learning laboratory ..
 +
http://archive.ics.uci.edu/ml/datasets.html
 +
 +
[[Category:Matlab Neural Network Toolbox for Classification]]
 
[[Category:Downloadable SVM libraries in C and how to run in Matlab]]
 
[[Category:Downloadable SVM libraries in C and how to run in Matlab]]

Revision as of 10:38, 23 March 2008

You can find an example for classifying a data using Matlab in the following link

http://www.igi.tugraz.at/lehre/EW/tutorials/nnt_intro/index.html


In the file 'nnt_intro_classification.m' it creates NN with 5 hidden units, 3 output units, logsig activation function for each layer. You need to change the configuration to improve the performance and refer to the pdf file in the downloaded zipped file.



You can download SVM library in the following link http://www.csie.ntu.edu.tw/~cjlin/libsvm/

You need to download the following file from the link MATLAB A simple MATLAB interface LIBSVM authors at National Taiwan University. 2.85 Zip

When you run 'make_win.m' in the Matlab command prompt it will generate dll files which are callable in Matlab. Before running 'make_win.m' you need to setup the default compiler used by mex by running 'mex -setup'

Datasets at UCI Irwin Machine Learning laboratory .. http://archive.ics.uci.edu/ml/datasets.html

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