diff --git a/kfoldCV.m b/kfoldCV.m
index 2aebb22..8f5c5be 100644
--- a/kfoldCV.m
+++ b/kfoldCV.m
@@ -4,7 +4,7 @@
     parfor cExp=1:2*cExpMax+1
         c=2^(cExp-cExpMax-1);
 
-        randomMapping=randperm(size(trainingData,1));
+        randomMapping=transpose(randperm(size(trainingData,1)));
         accurancy=zeros(k,3);
 
         for i=1:k
@@ -12,6 +12,7 @@
             testData=trainingData(mod(randomMapping,k)+1==i,:,:);
             trainClasses=classification(mod(randomMapping,k)+1~=i);
             testClasses=classification(mod(randomMapping,k)+1==i);
+            %fprintf('i=%i, k=%i, c=%i\n',i,k,c)
             [trainClasses,trainData]=balanceClasses(trainClasses,trainData,noClasses,0.00001);
             model=svmtrain(trainClasses,trainData(:,:),sprintf('-t 0 -c %f -q',c));
             [~, accurancy(i,:), ~]=svmpredict(testClasses, testData(:,:), model,'-q');
diff --git a/read.m b/read.m
index 0d915ec..3dd02f9 100644
--- a/read.m
+++ b/read.m
@@ -32,7 +32,7 @@
 
 smoothClassification=zeros(size(classificationWithPause));
 for i=1:size(classificationWithPause,1)
-    smoothClassification(i)=round(mean(classificationWithPause(max(i-round(1/window),1):min(i+round(1/window),end))));       
+    smoothClassification(i)=round(mode(classificationWithPause(max(i-2,1):min(i+2,end))));       
 end
 
 clear classificationWithPause
@@ -42,7 +42,7 @@
 classification=smoothClassification(smoothClassification~=-1);
 
 clear smoothClassification i
-save /home/jph/Uni/masterarbeit/data/AO1200msWindow50msShift.mat
+save /home/jph/Uni/masterarbeit/data/AO1200msWindow.mat
 
 
 disp('end')
diff --git a/svm.m b/svm.m
index 27c3fe8..7be527c 100644
--- a/svm.m
+++ b/svm.m
@@ -8,13 +8,13 @@
 window=0.2;
 shift=0.05;
 
-load('/home/jph/Uni/masterarbeit/data/AO1.mat');
+load('/home/jph/Uni/masterarbeit/data/AO1200msWindow.mat');
 
 %k=2; 
-maxExpC=5; % c\in {2^i|i=-maxExpC:1:maxExpC}
+%maxExpC=0; % c\in {2^i|i=-maxExpC:1:maxExpC}
 
 %choose to estimate based on EEG or EMG
-trainingData=trainingDataEEG;
+trainingData=trainingDataEMG;
 clear trainingDataEEG;
 clear trainingDataEMG;