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diff --git a/FEAST/FSToolbox/RELIEF.m b/FEAST/FSToolbox/RELIEF.m
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+% RELIEF - Kira & Rendell 1992
+% T is number of patterns to use
+% Defaults to all patterns if not specified.
+%
+% The license is in the license.txt provided.
+%
+% function w = RELIEF( data, labels, T ) 
+%
+function [w bestidx] = RELIEF ( data, labels, T )
+
+if ~exist('T','var')
+    T=size(data,1);
+end
+
+idx = randperm(length(labels));
+idx = idx(1:T);
+
+w = zeros(size(data,2),1);
+for t = 1:T
+    
+    x = data(idx(t),:);
+    y = labels(idx(t));
+    
+    %copy the x
+    protos = repmat(x, length(labels), 1);
+    %measure the distance from x to every other example
+    distances = [sqrt(sum((data-protos).^2,2)) labels];
+    %sort them according to distances (find nearest neighbours)
+    [distances originalidx] = sortrows(distances,1);
+   
+    foundhit = false;  hitidx=0;
+    foundmiss = false; missidx=0;
+    i=2; %start from the second one
+    while (~foundhit || ~foundmiss)
+
+        if distances(i,2) == y
+            hitidx = originalidx(i);
+            foundhit = true;
+        end
+        if distances(i,2) ~= y
+            missidx = originalidx(i);
+            foundmiss = true;
+        end
+        
+        i=i+1;
+
+    end
+    
+    alpha = 1/T;
+    for f = 1:size(data,2)%each feature
+        hitpenalty  = (x(f)-data(hitidx,f))  / (max(data(:,f))-min(data(:,f)));
+        misspenalty = (x(f)-data(missidx,f)) / (max(data(:,f))-min(data(:,f)));
+        
+        w(f) = w(f) - alpha*hitpenalty^2 + alpha*misspenalty^2;
+    end
+    
+end
+
+[~,bestidx] = sort(w,'descend');
+
+