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diff --git a/FEAST/MIToolbox/demonstration_algorithms/mRMR_D.m b/FEAST/MIToolbox/demonstration_algorithms/mRMR_D.m
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+++ b/FEAST/MIToolbox/demonstration_algorithms/mRMR_D.m
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+function selectedFeatures = mRMR_D(k, featureMatrix, classColumn)
+%function selectedFeatures = mRMR_D(k, featureMatrix, classColumn)
+%
+%Selects optimal features according to the mRMR-D algorithm from 
+%"Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy"
+%by H. Peng et al. (2005)
+%
+%Calculates the top k features
+%a dataset featureMatrix with n training examples and m features
+%with the classes held in classColumn (an n x 1 vector)
+
+noOfTraining = size(classColumn,1);
+noOfFeatures = size(featureMatrix,2);
+unselectedFeatures = ones(noOfFeatures,1);
+
+classMI = zeros(noOfFeatures,1);
+answerFeatures = zeros(k,1);
+highestMI = 0;
+highestMICounter = 0;
+currentHighestFeature = 0;
+
+featureMIMatrix = -(ones(k,noOfFeatures));
+
+%setup the mi against the class
+for n = 1 : noOfFeatures
+  classMI(n) = mi(featureMatrix(:,n),classColumn);
+	if classMI(n) > highestMI
+		highestMI = classMI(n);
+		highestMICounter = n;
+	end
+end
+
+answerFeatures(1) = highestMICounter;
+unselectedFeatures(highestMICounter) = 0;
+
+%iterate over the number of features to select
+for i = 2:k
+  score = -100;
+	currentHighestFeature = 0;
+	iMinus = i-1;
+  for j = 1 : noOfFeatures
+		if unselectedFeatures(j) == 1
+			currentMIScore = 0;
+			for m = 1 : iMinus
+        if featureMIMatrix(m,j) == -1
+          featureMIMatrix(m,j) = mi(featureMatrix(:,j),featureMatrix(:,answerFeatures(m)));
+        end
+				currentMIScore =  currentMIScore + featureMIMatrix(m,j);
+			end
+			currentScore = classMI(j) - (currentMIScore/iMinus);
+			
+			if (currentScore > score)
+				score = currentScore;
+				currentHighestFeature = j;
+			end
+		end
+	end
+	
+  if score < 0 
+    disp(['at selection ' int2str(j) ' mRMRD is negative with value ' num2str(score)]);
+  end
+
+	%now highest feature is selected in currentHighestFeature
+	%store it
+	unselectedFeatures(currentHighestFeature) = 0;
+	answerFeatures(i) = currentHighestFeature;
+end
+
+selectedFeatures = answerFeatures;