Infinite Feature Selection

Version 4.2 (4.05 KB) by Giorgio
InfFS allows you to rank a huge list of feature, even more than 40000 features and 10000 samples.
1.5K Downloads
Updated 21 Dec 2016

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The Inf-FS is a graph-based method which exploits the convergence properties of the power series of matrices to evaluate the importance of a feature with respect to all the other ones taken together. Indeed, in the Inf-FS formulation, each feature is mapped on an affinity graph, where nodes represent features and weighted edges relationships between them. Each path of a certain length l over the graph is seen as a possible selection of features. Therefore, varying these paths and letting them tend to an infinite number permits the investigation of the importance of each possible subset of features. The Inf-FS assigns a final score to each feature of the initial set; where the score is related to how much the given feature is a good candidate regarding the classification task. Therefore, ranking in descendant order the outcome of the Inf-FS allows us to perform the subset feature selection throughout a model selection stage to determine the number of features to be selected.
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Reference : Infinite Feature Selection
Link Paper :http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7410835
ResearchGate: https://www.researchgate.net/publication/282576688_Infinite_Feature_Selection
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Cite As

Giorgio (2024). Infinite Feature Selection (https://www.mathworks.com/matlabcentral/fileexchange/54763-infinite-feature-selection), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014b
Compatible with any release
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Version Published Release Notes
4.2

+ Infinite Feature Selection Dec. 2016: "Unsupervised" & "Supervised" versions.

4.0.0.0

New methods
[1] InfFS
[2] ECFS
[3] mrmr
[4] relieff
[5] mutinffs
[6] fsv
[7] laplacian
[8] mcfs
[9] rfe
[10] L0
[11] fisher
[12] UDFS
[13] llcfs
[14] cfs

3.0.0.0

- Added new method: Features Selection via Eigenvector Centrality (ECFS) 2016
- Updated the Infinite Feature Selection (InfFS) - Strong improvments on ranking accuracy 2016

2.2.0.0

- New Inf-FS
- Added 9 feature Selection methods such as: SVM-RFE, Relief-F, mRMR, Laplacian, L0, FSV, Fisher, etc...
- Make file (C/C++ Compiler required)

1.6.0.0

- some problems fixed

1.5.0.0