| title | author | date |
|---|---|---|
ThresholdFuzzyRoughQuickReduct |
Javad Rahimipour Anaraki |
23/05/18 |
To determine the most important features using an improved version of Fuzzy-Rough QuickReduct algorithm as described in Improving fuzzy-rough quick reduct for feature selection By Javad Rahimipour Anaraki and Mahdi Eftekhari
More info can be found in Novel Improvements on the Fuzzy-Rough QuickReduct Algorithm
This code can be run using MATLAB R2006a and above
To run the code, open main.m and choose a dataset to apply the method to. At first, the overall dependency degree is calculated using dependency.m. Then, indisernible objects are determined and returned to main.m. Finally, feature are selected if they have the best dependecy degree among all. This process stops if (overall dependency degree - current dependency degree) x number of samples < 1 or maximum dependency degree does not improve with adding extra features.
All datasets are stored in Data folder and originally adopted from UCI Machine Learning Repository
Datasets should have no column and/or row names, and the class values should be all numeric