Hello,
I try to use this programm but I am totally new to matlab (but have experience in R). When I call the function
mrmr_mid_d (variables, response, 25)
the following error occurs:
??? Undefined function or method 'mrmr_mid_d' for input arguments of type 'double'.
The same occures when I convert my data in int8 or single.

something similar happens when I try to use the demo_mi.m :

mutualinfo(a,b)
??? Undefined function or method 'estpab' for input arguments of type 'double'.
Error in ==> mutualinfo at 21
[p12, p1, p2] = estpab(vec1,vec2);

I think my problem is very a very basic one because I do not know anything about Matlab.
Could anybody please help me. It is very important for me to use this programm and the online version does not work with my data set because it is too large.

Hi All,
For those who can't run the demo file because of 'undefined function' error. You need to:
1) Run this command: list = dir('*.cpp');
to get the list of files.
2) For all the files in list, change log(2) to log(2.0). You can get all the files' names by:
for i=1:length(list)
list(i).name
end
2) Run 'makeosmex.m'
Now this should works like a dream.

Comment only

06 Jun 2014

Mutual Information computation
A self-contained package for computing mutual information, joint/conditional probability, entropy

I got following error, on running demo_mi.m
Undefined function 'estpab' for input arguments of type 'double'.
Error in mutualinfo (line 21)
[p12, p1, p2] = estpab(vec1,vec2);
Error in demo_mi (line 25)
mutualinfo(a,b)
What's wrong ?

Comment only

02 Jun 2014

Mutual Information computation
A self-contained package for computing mutual information, joint/conditional probability, entropy

I also get the problem "Undefined function 'estpa' for input arguments of type 'double'". I find the estpa is cpp file which is a C++ file. I use Win8 62 bit application and Matlab 2011b. What's wrong with it?

1

28 May 2014

Mutual Information computation
A self-contained package for computing mutual information, joint/conditional probability, entropy

when the range of the features vectors is large, let's say 1-10000 estpab() calculates probibilty density with the same length (10000 in this case). Now if both feature vectors have a large range, lets say the other one is 1-10000 too, then the joint pdf computed by estpab is a 10000 x 10000 matrix and the computation if MI takes very long time. Is there a way to modify the algorithm in order to avoid this problem?

Comment only