1 files changed, 0 insertions, 73 deletions
diff --git a/FEAST/MIToolbox/demonstration_algorithms/DISR.m b/FEAST/MIToolbox/demonstration_algorithms/DISR.m
deleted file mode 100644
index c8f5669..0000000
--- a/FEAST/MIToolbox/demonstration_algorithms/DISR.m
+++ /dev/null
@@ -1,73 +0,0 @@
-function selectedFeatures = DISR(k, featureMatrix, classColumn)
-%function selectedFeatures = DISR(k, featureMatrix, classColumn)
-%
-%Computers optimal features according to DISR algorithm from 
-%On the Use of variable "complementarity for feature selection" 
-%by P Meyer, G Bontempi (2006)
-%
-%Computes the top k features from
-%a dataset featureMatrix with n training examples and m features
-%with the classes held in classColumn.
-%
-%DISR - arg(Xi) max(sum(Xj mem XS)(SimRel(Xij,Y)))
-%where SimRel = MI(Xij,Y) / H(Xij,Y)
-
-totalFeatures = size(featureMatrix,2);
-classMI = zeros(totalFeatures,1);
-unselectedFeatures = ones(totalFeatures,1);
-score = 0;
-currentScore = 0;
-innerScore = 0;
-iMinus = 0;
-answerFeatures = zeros(k,1);
-highestMI = 0;
-highestMICounter = 0;
-currentHighestFeature = 0;
-
-%create a matrix to hold the SRs of a feature pair. 
-%initialised to -1 as you can't get a negative SR.
-featureSRMatrix = -(ones(k,totalFeatures));
-
-for n = 1 : totalFeatures
-	classMI(n) = mi(featureMatrix(:,n),classColumn);
-	if classMI(n) > highestMI
-		highestMI = classMI(n);
-		highestMICounter = n;
-	end
-end
-
-answerFeatures(1) = highestMICounter;
-unselectedFeatures(highestMICounter) = 0;
-
-for i = 2 : k
-	score = 0;
-	currentHighestFeature = 0;
-	iMinus = i-1;
-  for j = 1 : totalFeatures
-		if unselectedFeatures(j) == 1
-			%DISR - arg(Xi) max(sum(Xj mem XS)(SimRel(Xij,Y)))
-			%where SimRel = MI(Xij,Y) / H(Xij,Y)
-			currentScore = 0;
-			for m = 1 : iMinus
-        if featureSRMatrix(m,j) == -1
-          unionedFeatures = joint([featureMatrix(:,answerFeatures(m)),featureMatrix(:,j)]);
-				  tempUnionMI = mi(unionedFeatures,classColumn);
-				  tempTripEntropy = h([unionedFeatures,classColumn]);
-				  featureSRMatrix(m,j) = tempUnionMI/tempTripEntropy;
-        end
-        
-				currentScore =  currentScore + featureSRMatrix(m,j);
-			end
-			if (currentScore > score)
-				score = currentScore;
-				currentHighestFeature = j;
-			end
-		end
-	end
-	%now highest feature is selected in currentHighestFeature
-	%store it
-	unselectedFeatures(currentHighestFeature) = 0;
-	answerFeatures(i) = currentHighestFeature;
-end
-
-selectedFeatures = answerFeatures;