Mutual information

Mrmr feature selection (using mutual information computation) in matlab

The following Matlab project contains the source code and Matlab examples used for mrmr feature selection (using mutual information computation). This package is the mRMR (minimum-redundancy maximum-relevancy) feature selection method in (Peng et al, 2005 and Ding & Peng, 2005, 2003), whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent publications.

Calculates the sample entropy, in bits, of discrete variables. in matlab

The following Matlab project contains the source code and Matlab examples used for calculates the sample entropy, in bits, of discrete variables. . Entropy: Returns entropy (in bits) of each column of 'X'   by Will Dwinnell     H = Entropy(X)     H = row vector of calculated entropies (in bits)   X = data to be analyzed     Note 1: Each distinct value in X is considered a unique value.

Mutual information in matlab

The following Matlab project contains the source code and Matlab examples used for mutual information. MutualInformation: returns mutual information (in bits) of discrete variables 'X' and 'Y'   I = MutualInformation(X,Y);     I = calculated mutual information (in bits)   X = variable(s) to be analyzed (column vector)   Y = variable to be analyzed (column vector)     Note 1: Multiple variables may be handled jointly as columns in     matrix 'X'.

Information theory toolbox in matlab

The following Matlab project contains the source code and Matlab examples used for information theory toolbox. This toolbox contains functions for discrete random variables to compute following quantities: 1)Entropy 2)Joint entropy 3)Conditional entropy 4)Relative entropy (KL divergence) 5)Mutual information 6)Normalized mutual information 7)Normalized variation information This toolbox is a tweaked and bundled version of my previous submissions.

Ecological information based approach in matlab

The following Matlab project contains the source code and Matlab examples used for ecological information based approach. This is a simple code for calculating the number of nodes, Total System Throughput (TST), Average Mutual Information (AMI), conditional entropy, effective connectivity, and effective number of roles of information flow based network represented in the form of a matrix.

Information theoretic feature selection in matlab

The following Matlab project contains the source code and Matlab examples used for information theoretic feature selection. Description: Code (Matlab/C++ Mex) for the following MI based feature selection approaches: - Maximum relevance (maxRel) - Minimum redundancy maximum relevance (MRMR) - Minimum redundancy (minRed) - Quadratic programming feature selection (QPFS) - Mutual information quotient (MIQ) - Maximum relevance minimum total redundancy (MRMTR) or extended MRMR (EMRMR) - Spectral relaxation global Conditional Mutual Information (SPEC_CMI)

Sum of conditional variance in matlab

The following Matlab project contains the source code and Matlab examples used for sum of conditional variance. Sum of Conditional Variance (SCV) is a new similarity metric for multi-modal image registration, eg CT-Fluoroscopy registration. This is derived using Joiint probability distribution but it is readily differentiable unline Mutual information (MI)
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