%######################### [Cosine similarity without similarity] ################################
x0 = [ 0.7760055874299497 0.7970390958864669 0.8408940576530042 0.8333843941721516 0.80505200342914 0.7960842492891936 0.8217204101409811 0.8406919131003536 0.8354164015399785 0.821604459308682 0.8517715928102071 0.7800683985224287 0.7163463241105336 0.8368631321669582 0.8540577324879249 0.9018637237920049 0.8158940057429225 0.8667594964365042 0.8222556787075642 0.9032165303937582 0.848880343267065 0.9270242212554809 0.9149794374716309 0.8645201546681106];

%######################### [Cosine similarity with similarity] ################################
x1 = [ 0.8515562163171859 0.8517856257787365 0.8471129456361841 0.8218128216869616 0.7994368088447924 0.8065215038249249 0.8281251269515378 0.8706046186253577 0.8442875635715913 0.6856602646265952 0.6961819212124306 0.7950383316037629 0.7792361787880172 0.7379791422625895 0.8160219269179515 0.9077667390887688 0.8903705728958488 0.8968949177184907 0.8852672270639651 0.9024676067637735 0.8047376155895887 0.9303236165563551 0.8814046441073135 0.9176600151463739];

%bar([x0;x1;x2;x3]') %with kendall tau
bar([x0;x1]')
xlabel('Participant')
ylabel('Agreement')
axis([0 25 0 1])
%axis([0 10 -1 1]) %for kendall tau
legend('without filtering criteria','with filtering criteria','Location','NorthWest')
set(gca,'XTick',0:1:25)

%x = rand(30,1);
%bar(x)
fprintf('Without Filter -\t avg: %.3f, Std dev: %.3f\n',mean(x0),std(x0));
fprintf('With Filter -\t\t avg: %.3f, Std dev: %.3f\n',mean(x1),std(x1));

Without Filter -	 avg: 0.836, Std dev: 0.048
With Filter -		 avg: 0.835, Std dev: 0.065

Published with MATLAB® 7.13