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-MIToolbox v1.03 for C/C++ and MATLAB/OCTAVE
-
-The MIToolbox contains a set of functions to calculate information theoretic
-quantities from data, such as the entropy and mutual information.  The toolbox
-contains implementations of the most popular Shannon entropies, and also the
-lesser known Renyi entropy.  The toolbox only supports discrete distributions,
-as opposed to continuous. All real-valued numbers will be processed by x = floor(x)
-
-These functions are targeted for use with feature selection algorithms rather 
-than communication channels and so expect all the data to be available before 
-execution and sample their own probability distributions from the data.
-
-Things you can do:
- - Entropy
- - Conditional Entropy
- - Mutual Information
- - Conditional Mutual Information
- - generating a joint variable
- - generating a probability distribution from a discrete random variable
- - Renyi's Entropy
- - Renyi's Mutual Information
-
-Note: all functions are calculated in log base 2, so return units of "bits".
-
-======
-
-Examples:
-
->> y = [1 1 1 0 0]';
->> x = [1 0 1 1 0]';
-
->> mi(x,y)       %% mutual information I(X;Y)
-ans =
-    0.0200
-
->> h(x)          %% entropy H(X)
-ans =
-    0.9710
-
->> condh(x,y)    %% conditional entropy H(X|Y)
-ans =
-    0.9510
-
->> h( [x,y] )    %% joint entropy H(X,Y)
-ans =
-    1.9219
-
->> joint([x,y])  %% joint random variable XY
-ans =
-     1
-     2
-     1
-     3
-     4
-
-======
-
-To compile the library for use in MATLAB/OCTAVE, execute CompileMIToolbox.m
-from within MATLAB, or run 'make matlab' from a terminal.
-
-To compile the library for C/C++, run 'make' at a terminal.
-
-The C source files are licensed under the LGPL v3. The MATLAB wrappers and 
-demonstration feature selection algorithms are provided as is with no warranty 
-as examples of how to use the library in MATLAB.
-
-Update History
-08/11/2011 - v1.03 - Minor documentation changes to accompany the JMLR publication.
-15/10/2010 - v1.02 - Fixed bug where MIToolbox would cause a segmentation fault if a x by 0 empty matrix was passed in. Now prints an error message and returns gracefully
-02/09/2010 - v1.01 - Updated CMIM.m in demonstration_algorithms, due to a bug where the last feature would not be selected first if it had the highest MI
-07/07/2010 - v1.00 - Initial Release