Minor output changes

spike_sorting.m

@@ -2,8 +2,8 @@
 %% EMAIL[1]  : apostolof@auth.gr
 %% AUTHOR[2] : Charalampos Papadiakos (8302)
 %% EMAIL[2]  : charaldp@ece.auth.gr
-%% AUTHOR[3] : Hlektra Mitsi ()
-%% EMAIL[3]  :
+%% AUTHOR[3] : Hlektra Mitsi (8536)
+%% EMAIL[3]  : ilektraem@auth.ece.gr
 %% $DATE     : 28-December-2018 12:45:00 $
 %% $Revision : 1.00 $
 %% DEVELOPED : 9.0.0.341360 (R2016a)
@@ -111,6 +111,7 @@ clear(clearvars{:})
 clear clearvars
 
 for fileIndex=1:4
+    fprintf('========================================================\n');
     fprintf('Loading evaluation dataset no. %d\n', fileIndex);
     filename = sprintf('dataset\\Data_Eval_E_%d.mat', fileIndex);
     Dataset = load(filename);
@@ -257,7 +258,7 @@ for fileIndex=1:4
     
     %% Q.2.5
     accuracy = MyClassify(features, spikeClass');
-    fprintf('Accuracy achieved is %.2f%%\n\n', accuracy);
+    fprintf('Accuracy achieved is %.2f%%\n', accuracy);
     
     % clustering using DB-SCAN algorithm
     % code for DB-SCAN downloaded from here:
@@ -304,7 +305,7 @@ for fileIndex=1:4
     xlabel('PCA feature 1');
     ylabel('PCA feature 2');
     accuracy = classperf(spikeClass',dbScanClasses);
-    fprintf('Accuracy achieved with DB-SCAN is %.2f%%\n\n', accuracy.CorrectRate*100);
+    fprintf('Accuracy achieved with DB-SCAN is %.2f%%\n', accuracy.CorrectRate*100);
     
     % hierarchical clustering
     distances = pdist(features(:, 6:7));
@@ -331,7 +332,7 @@ for fileIndex=1:4
     xlabel('PCA feature 1');
     ylabel('PCA feature 2');
     accuracy = classperf(spikeClass',hierarchicalClusters);
-    fprintf('Accuracy achieved with hierarchical clustering is %.2f%%\n\n', accuracy.CorrectRate*100);
+    fprintf('Accuracy achieved with hierarchical clustering is %.2f%%\n', accuracy.CorrectRate*100);
     
     % clustering using kmeans algorithm
     rng(1); % For reproducibility