1 files changed, 0 insertions, 69 deletions
diff --git a/FEAST/MIToolbox/demonstration_algorithms/mRMR_D.m b/FEAST/MIToolbox/demonstration_algorithms/mRMR_D.m
deleted file mode 100644
index 50b14bc..0000000
--- a/FEAST/MIToolbox/demonstration_algorithms/mRMR_D.m
+++ /dev/null
@@ -1,69 +0,0 @@
-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;