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This is an implementation of SUFFUSE: Simultaneous Fuzzy-Rough Feature-Sample Selection

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SUFFUSE
Javad Rahimipour Anaraki
13/08/18

Use case

To determine the most important features and samples simultanously using Shuffled Frog Leaping Algorithm as described in SUFFUSE: Simultaneous Fuzzy-Rough Feature-Sample Selection By Javad Rahimipour Anaraki, Saeed Samet, Jeon-Hyun Lee and Chang Wook Ahn

Compile

This code can be run using MATLAB R2006a and above

Run

To run the program open main.m in MATLAB, choose any dataset (by considering the requirements stated in the Note section of this page), and hit F5.

All datasets are stored in data folder and originally adopted from UCI Machine Learning Repository.

Note

Datasets end with OK.csv in their names should have no column and/or row names, the first column should be row number, and the class values should be numeric. The ones ending with W.csv should have columns name and the class values should be alphabetical.

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This is an implementation of SUFFUSE: Simultaneous Fuzzy-Rough Feature-Sample Selection

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