Feature Selection Package - Algorithms - Relief-F
Relief-F is a feature selection strategy that chooses instances randomly, and changed the weights of the feature relevance based on the nearest neighbor. By its merits, Relief-F is one of the most successful strategies in feature selection.
Method Signature:
[out] = fsReliefF(X, Y, k, m)

   out: A struct containing the following fields:
    X: The features on current trunk, each column is a feature vector on all instances, and each row is a part of the instance.
    Y: The label of instances, in single column form: 1 2 3 4 5 ...
    k: The size of the neighborhood you wish to evaluate.
    m: How many samples you want to try.
Code Example
% Using the wine.dat data set, which can be found at
% [fspackage_location]/classifiers/knn/wine.mat
Keyword in Evaluator Framework
BibTex entry for:

Computational Methods of Feature Selection by Huan Liu and Hiroshi Motoda.
    title = {Computational Methods of Feature Selection},
   editor = {Liu, H. and Motoda, H.},
    publisher = {Chapman & Hall},
   year = {2008}