Rank: 634 based on 171 downloads (last 30 days) and 3 files submitted
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Dimitrios Ververidis

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Company/University
CERTH - Centre for Research and Technology Hellas
Lat/Long
40.568, 22.997

Personal Profile:

He graduated from the Dept. of Mathematics of the Aristotle University of Thessaloniki in 2001. He continued his studies at the School of Medicine of the same University until 2003, where he obtained the M.Sc. in Medical Informatics. In 2008, he obtained the Ph.D. in Informatics entitled as "Digital Processing Techniques in Speech Emotion Recognition" at the Computer Science faculty of the same University. He served in the Army during 2008-2009. He has been awarded the ERCIM fellowship for 2009-2011. In 2009, he was with VTT Technical Research Center of Finland working on Alzeimer's disease and Neurally Adjusted Ventilation Assist (NAVA). In 2010-2011, he was with IAIS Fraunhofer Institute in Bonn working on Speech Analysis. He is currently a researcher in CERTH, Centre for Research and Technology Hellas working on Augmented Reality for Android devices.

Professional Interests:
Speech Processing, Pattern Recognition, Android, Augmented Reality

 

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Files Posted by Dimitrios View all
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(last 30 days)
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24 Feb 2011 Information loss of the Mahalanobis distance in high dimensions: Matlab implementation Information loss estimation to set a lower limit on classification rate. Author: Dimitrios Ververidis pattern recognition, gaussian methods, feature selection, information loss, high dimensionality p... 12 1
29 Aug 2010 Screenshot Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis demo, gui, signal processing, image processing, modeling 136 38
  • 3.66667
3.7 | 16 ratings
04 May 2009 Screenshot Gaussian Mixture Modeling GUI (GMM DEMO) GUI for an Expectation-Maximization algorithm (EM) variant (Split-EM-Discriminant) Author: Dimitrios Ververidis demo, gui, image processing, mathematics, optimization, signal processing 23 3
  • 4.0
4.0 | 1 rating
Comments and Ratings by Dimitrios View all
Updated File Comments Rating
25 May 2012 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis

The problem is that Matlab is not compatible with previous versions.
The problem is within 'gui_mainfcn.m'

Solution:

Backward compatabily for Matlab <7.5 for code written with >7.7 ****
HINT: if you have Matlab 7.5 do this

go to 'gui_mainfcn.m' to line 226 and replace

226 guidemfile('restoreToolbarToolPredefinedCallback',gui_hFigure)

with

%----Check Matlab Version (Original on 7.7 support for 7.5 also) ---
MatlabVersion = version;
MatlabVersion = str2double(MatlabVersion(1:3));
%-------------------------------------------------------------------
if MatlabVersion >=7.7
guidemfile('restoreToolbarToolPredefinedCallback',gui_hFigure);
elseif MatlabVersion ==7.5
guidemfile('restoreToolbarToolPredefinedCallback',get(gui_hFigure));
end
%-------------------------------------------------------------------

with this way you have functionality for code written for either at older than 7.5 or newer than 7.7 :)

09 Jan 2012 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis

Go to options and make confidence interval smaller. This will increase the number of cross-validation repetitions, thus execution time gets longer. The features selected will be almost identical per run. This is due to the fact that cross-validation involves a random selection of training and testing set.

20 Sep 2010 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis

Response to Ly Lu:

The problem is that you used 'test' instead of 'test.mat' and therefore matlab can not find your file.

check if stringvariable DatasetToUse is 'test.mat'

01 Mar 2010 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis

Hi,

1)There is no missing end in the "DataLoadAndPreprocess.m". As regards the reduction of 114 features to 90, it is happening because there were some features with NaNs in the certain dataset that were removed.

You can remove such features (if you have NaNs of Infs in your data) by adding some lines in function DataLoadAndPreprocess.m.

2) Well, there was a minor bug:

At the ForwSel_main.mat replace lines 256 to 273 with the following:

if ~isempty(handles)
axes(handles.YelLinesAxes);
hold on
if (NPatterns > KFeatures)
axis([0 NPatterns 0 KFeatures]); axis manual
HYelLines(FeatureToInclude)=plot([0 NPatterns+2],...
(FeatureToInclude-0.5)*ones(1,2),'y','linewidth',3);
else
axis([0 KFeatures 0 NPatterns]); axis manual
HYelLines(FeatureToInclude)= plot(...
FeatureToInclude*ones(1,2),[0 KFeatures+2],'y','linewidth',3);
end
set(gca,'Visible','off');
drawnow
set(findobj(gcf,'Tag','ListSelFeats'), 'String', ...
sort(SelectedFeatPool));
axes(handles.FeatSelCurve);
end

3) There is no need to change the name of your data. It works with any name. For example I debugged the previous error by generating a two class problem of 200 patterns (100 per class) and 2000 features estimated on them:

>> x = [0.25+0.1*randn(100,2000); 0.35+0.25*randn(100,2000)];
>> Data = [x [ones(100,1); 2*ones(100,1)]];

That correspond to patternsXfeatures matrix 200 X 2000
and Targets vector 200 X 1

I saved the "Data" variable as "Data.mat" in the [PatTargMatrices] folder and I loaded it with the GUI and I pressed run.

I don't have the linux version of Matlab and I don't know the differences. I don't think that there is any.

BR,
Dimitrios

29 Dec 2009 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis

hi toto11,

1. Which coefficients ? Do you mean those in ReliefF function ? If you mean them, cross-correlation was not exploited.

2. Yes, you can use GA algorithm for feature selection:
a) add your function GenetAlgo.m in DEMO.m (similarly as ReliefF.m), e.g.
%=============================================

elseif strcmp(FSSettings.FSMethod,'ReliefF')
[FeatureWeightsOrdered, FeaturesIndexOrdered, ...
handles.OptimumFeatureSet] = ReliefF(handles.file,...
FSSettings,handles);
elseif strcmp(FSSettings.FSMethod,'GenetAlgo')
[FeatureWeightsOrdered, FeaturesIndexOrdered, ...
handles.OptimumFeatureSet] = GenetAlgo(handles.file,
FSSettings,handles);
%=================================================

Do not forget to add 'GenetAlgo' as a string option in the menu of figure. The default is 'SFS'.

Structure FSSettings.YourSettings allows the use of any variables for GA (mutation vars etc.).

NOTE: If you have managed to add it, please send it to me, I will acknowledge you (is there any more formal name than toto11?)

Comments and Ratings on Dimitrios' Files View all
Updated File Comment by Comments Rating
12 Aug 2014 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis alireza

hi all
thx for reply
i read all comment but i cant solve my problem
i save my dataset in this way
save ('feature.mat','feature')
but when i open this file in demo i faced to this error
Error using load
Unable to read file 'feature': no such file or directory.

Error in DataLoadAndPreprocess (line 21)
load([DatasetToUse]);

Error in DEMO>OpenDataFile_ClickedCallback (line 64)
[Patterns, Targets] = DataLoadAndPreprocess(handles.file);

Error in gui_mainfcn (line 96)
feval(varargin{:});

Error in DEMO (line 19)
gui_mainfcn(gui_State, varargin{:});

Error while evaluating uipushtool ClickedCallback
whats problem?what i must do it?

06 Jul 2014 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis mehdi

After using the Feature Selection, how can I use the selected features for classification, such that I can see the performance of classification?(How can I see the output of classification in workspace?)

19 May 2014 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis bjut

good

10 Mar 2014 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis Emad

After using the Feature Selection, how can I use the selected features for classification, such that I can see the performance of classification?(How can I see the output of classification in workspace?)

09 Jul 2013 Feature Selection using Matlab Select the subset of features that maximizes Correct Classification Rate. Author: Dimitrios Ververidis Yang, Lei

Very good

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