Craigacp-MIToolbox-2b18470
所属分类：matlab编程
开发工具：matlab
文件大小：61KB
下载次数：6
上传日期：2012-10-01 12:42:24
上 传 者：
mkannanofficial
说明： it is a toolbox which used for denoising
文件列表:
Craigacp-MIToolbox-2b18470 (0, 2012-08-30)
Craigacp-MIToolbox-2b18470\ArrayOperations.c (8656, 2012-08-30)
Craigacp-MIToolbox-2b18470\ArrayOperations.h (3873, 2012-08-30)
Craigacp-MIToolbox-2b18470\COPYING (35147, 2012-08-30)
Craigacp-MIToolbox-2b18470\COPYING.LESSER (7637, 2012-08-30)
Craigacp-MIToolbox-2b18470\CalculateProbability.c (11013, 2012-08-30)
Craigacp-MIToolbox-2b18470\CalculateProbability.h (4185, 2012-08-30)
Craigacp-MIToolbox-2b18470\CompileMIToolbox.m (345, 2012-08-30)
Craigacp-MIToolbox-2b18470\Entropy.c (3951, 2012-08-30)
Craigacp-MIToolbox-2b18470\Entropy.h (2733, 2012-08-30)
Craigacp-MIToolbox-2b18470\MIToolbox.h (1762, 2012-08-30)
Craigacp-MIToolbox-2b18470\MIToolbox.m (2533, 2012-08-30)
Craigacp-MIToolbox-2b18470\MIToolboxMex.c (15363, 2012-08-30)
Craigacp-MIToolbox-2b18470\Makefile (3551, 2012-08-30)
Craigacp-MIToolbox-2b18470\MutualInformation.c (3859, 2012-08-30)
Craigacp-MIToolbox-2b18470\MutualInformation.h (2564, 2012-08-30)
Craigacp-MIToolbox-2b18470\RenyiEntropy.c (5902, 2012-08-30)
Craigacp-MIToolbox-2b18470\RenyiEntropy.h (2654, 2012-08-30)
Craigacp-MIToolbox-2b18470\RenyiMIToolbox.m (1473, 2012-08-30)
Craigacp-MIToolbox-2b18470\RenyiMIToolboxMex.c (5915, 2012-08-30)
Craigacp-MIToolbox-2b18470\RenyiMutualInformation.c (3582, 2012-08-30)
Craigacp-MIToolbox-2b18470\RenyiMutualInformation.h (2343, 2012-08-30)
Craigacp-MIToolbox-2b18470\WeightedEntropy.c (4843, 2012-08-30)
Craigacp-MIToolbox-2b18470\WeightedEntropy.h (2926, 2012-08-30)
Craigacp-MIToolbox-2b18470\WeightedMIToolbox.m (2876, 2012-08-30)
Craigacp-MIToolbox-2b18470\WeightedMIToolboxMex.c (13439, 2012-08-30)
Craigacp-MIToolbox-2b18470\WeightedMutualInformation.c (4171, 2012-08-30)
Craigacp-MIToolbox-2b18470\WeightedMutualInformation.h (2676, 2012-08-30)
Craigacp-MIToolbox-2b18470\cmi.m (674, 2012-08-30)
Craigacp-MIToolbox-2b18470\condh.m (547, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms (0, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\CMIM.m (1372, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\CMIM_Mex.c (5081, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\DISR.m (2210, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\DISR_Mex.c (6223, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\IAMB.m (1325, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\compile_demos.m (310, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\mRMR_D.m (1970, 2012-08-30)
Craigacp-MIToolbox-2b18470\demonstration_algorithms\mRMR_D_Mex.c (5653, 2012-08-30)
... ...
MIToolbox v2.0 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 also provides implementations of
the weighted entropy and weighted mutual information from "Information Theory
with Application", S. Guiasu (1977). 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.
Functions contained:
- 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
- Weighted Entropy
- Weighted Mutual Information
- Weighted Conditional 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 use with C programs run 'make x86' for a 32-bit
library, or 'make x***' for a ***-bit library.
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
30/07/2011 - v2.00 - Added implementations of the weighted entropy and weighted
mutual information. More cleanup of Mex entry point
to further check the inputs.
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.
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