diff --git a/spike_sorting.m b/spike_sorting.m index 114764b..e972257 100644 --- a/spike_sorting.m +++ b/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) @@ -111,7 +111,8 @@ clear(clearvars{:}) clear clearvars for fileIndex=1:4 - fprintf('Loading evaluation dataset no. %d \n', fileIndex); + fprintf('========================================================\n'); + fprintf('Loading evaluation dataset no. %d\n', fileIndex); filename = sprintf('dataset\\Data_Eval_E_%d.mat', fileIndex); Dataset = load(filename); data = double(Dataset.data); @@ -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