Projects that are tagged with mutual information.


Logo FEAST 2.0.0

by apocock - January 8, 2017, 00:49:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 41074 views, 7338 downloads, 3 subscriptions

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:

Major refactoring of FEAST to improve speed and portability.

  • FEAST now clones the input data if it's floating point and discretises it to unsigned ints once in a single pass. This improves the speed by about 30%.
  • FEAST now has unsigned int entry points which avoid this discretisation and are much faster if the data is already categorical.
  • Added weighted feature selection algorithms to FEAST which can be used for cost-sensitive feature selection.
  • Added a Java API using JNI.
  • FEAST now returns the internal score for each feature according to the criterion. Available in all three APIs.
  • Rearranged the repository to make it easier to work with. Header files are now in `include`, source in `src`, the MATLAB API is in `matlab/` and the Java API is in `java/`.
  • FEAST now compiles cleanly using `-std=c89 -Wall -Werror`.

Logo MIToolbox 3.0.0

by apocock - January 8, 2017, 00:43:22 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 30308 views, 5111 downloads, 3 subscriptions

About: A mutual information library for C and Mex bindings for MATLAB. Aimed at feature selection, and provides simple methods to calculate mutual information, conditional mutual information, entropy, conditional entropy, Renyi entropy/mutual information, and weighted variants of Shannon entropies/mutual informations. Works with discrete distributions, and expects column vectors of features.

Changes:

Major refactor of code and reorganised the repository so it's a little more sensible.

  • Refactored all C functions to expose a version which takes unsigned integer inputs.
  • Rearranged the repository to separate out headers from source, and MATLAB code from C library code.

Minor changes:

  • General code cleanup to reduce duplicated code.
  • Adding an COMPILE_R flag to go with the COMPILE_C flag, to make it easier to produce an R wrapper.
  • All code now compiles cleanly with "-std=c89 -Wall -Werror".

Logo JMLR Information Theoretical Estimators 0.63

by szzoli - June 9, 2016, 23:42:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 122286 views, 22467 downloads, 3 subscriptions

About: ITE (Information Theoretical Estimators) is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities and kernels on distributions. Thanks to its highly modular design, ITE supports additionally (i) the combinations of the estimation techniques, (ii) the easy construction and embedding of novel information theoretical estimators, and (iii) their immediate application in information theoretical optimization problems.

Changes:
  • Conditional Shannon entropy estimation: added.

  • Conditional Shannon mutual information estimation: included.