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Add calculations on the classification results using skewness or kurtosis.
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Figures/generate_figure10.m

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set(gcf,'color','w');
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set(gca,'FontSize',12);
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%% Skewness
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th = 1.0;
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true_class = data(:,4) < 0.1 & data(:,5)<0.1;
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pred_class = data(:,14) > th;
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C = confusionmat(true_class,pred_class);
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figure(1001)
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subplot(1,2,1), confusionchart(C,{'ND','D'},'Normalization','row-normalized','GridVisible','off','XLabel','')
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title('Skew > 0.9 (row normalized)')
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set(gcf,'color','w');
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set(gca,'FontSize',12);
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%
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subplot(1,2,2), confusionchart(C,{'ND','D'},'Normalization','column-normalized','GridVisible','off')
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title('Skew > 0.9 (column normalized)')
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set(gcf,'color','w');
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set(gca,'FontSize',12);
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%% Kurtosis
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th = 7.5;
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true_class = data(:,4) < 0.1 & data(:,5)<0.1;
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pred_class = data(:,15) > th;
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C = confusionmat(true_class,pred_class);
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figure(1002)
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subplot(1,2,1), confusionchart(C,{'ND','D'},'Normalization','row-normalized','GridVisible','off','XLabel','')
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title('Kurt > 0.9 (row normalized)')
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set(gcf,'color','w');
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set(gca,'FontSize',12);
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%
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subplot(1,2,2), confusionchart(C,{'ND','D'},'Normalization','column-normalized','GridVisible','off')
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title('Kurt > 0.9 (column normalized)')
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set(gcf,'color','w');
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set(gca,'FontSize',12);
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