I am facing difficulty using the code. I am running Matlab 7, on Mac OS. When i call the function I get the following error :

"
??? Error using ==> vertcat
CAT arguments dimensions are not consistent.
Error in ==> statistics at 9
Hy=entropia2([y;zeros(1,C)],15);
Error in ==> GA_feature_selector at 19
[Hx,Hy,MIxy,MIxx]=statistics(X,y);
"

to avoid the error when calling sparse function, just invert x (and y) with 1.
Mx=sparse(idx,1,x,n,k,n);
Please next time refer to the help of sparse function before asking :)

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04 Dec 2014

Information Theory Toolbox
Functions for Information theory, such as entropy, mutual information, KL divergence, etc

Is the output of the conditionalEntropy function a normalized value? I ask this because, I computed conditional entropy myself with the aid of MutualInformation function and MATLAB's entropy() method. I had got values of conditional Entropy to be greater than 1, which was expected. However, I am getting all conditional entropy values < 1 using InfoTheory toolbox's conditonalEntropy() function.
Has the output been normalized?
Please let me know. Thanks

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07 Oct 2014

Information Theory Toolbox
Functions for Information theory, such as entropy, mutual information, KL divergence, etc

Very useful and efficient toolbox, thank you. However, there is a bug in the nmi.m. last sentence should read:
z = sqrt((MI/Hx)*(MI/Hy));
Output variable is "z" and not "v". But this is obvious a typo, so it does not influence my rating.

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