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EXC: small updates

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nno committed Jul 25, 2019
1 parent 3f0c13d commit bb246c3f44a4d8ea3c65cd828fd9903416479c89
@@ -16,7 +16,7 @@ Overview
contents_demo
get_started
download
labman2017
nmsm2019
faq
contact
contribute
@@ -157,15 +157,15 @@ Monday
17:40-18:30 Optional: discuss your data models
-------------- ---------------------------------------------------------------------------------------------------
Tuesday
09:00 :doc:`ex_classify_lda`, :doc:`ex_nfold_crossvalidation`. Optional :doc:`ex_classify_double_dipping`
09:00 :doc:`ex_classify_lda`, :doc:`ex_nfold_crossvalidation`.
-------------- ---------------------------------------------------------------------------------------------------
10:30 Coffee break
-------------- ---------------------------------------------------------------------------------------------------
11:00 CoSMoMPVA measures part 1. :doc:`ex_measures`
11:00 :doc:`ex_measures`
-------------- ---------------------------------------------------------------------------------------------------
12:30 Lunch break
-------------- ---------------------------------------------------------------------------------------------------
14:00 CoSMoMPVA measures part 2. :doc:`ex_measures`
14:00 :doc:`ex_classify_double_dipping`, :doc:`ex_neighborhood` first part
-------------- ---------------------------------------------------------------------------------------------------
15:30 Coffee break
-------------- ---------------------------------------------------------------------------------------------------
@@ -5,8 +5,8 @@
% results double dipping to interpret results for a real analysis that you
% would publish.

nfeatures=10;
nsamples_per_class=20;
nfeatures=100;
nsamples_per_class=200;
nclasses=2;
niter=1000;

@@ -109,6 +109,7 @@
% classification accuracy)
% (Below, in the for-loop, the field 'classifier' is set for each function
% handle in the cell 'classifiers')
% Assign the struct to a variable named args.

% >@@>
args=struct();
@@ -158,7 +159,6 @@
desc=sprintf('%s: accuracy %.1f%%', classifier_name, accuracy*100);
title(desc)


classes = {'monkey','lemur','mallard','warbler','ladybug','lunamoth'};
nclasses=numel(classes);
set(gca,'XTick',1:nclasses,'XTickLabel',classes);
@@ -54,14 +54,19 @@

%%

% set the target (trial condition)
% set the targets in ds.sa.targets (trial condition)
% Hint: use the first column from ds.sa.trialinfo
% >@@>
ds.sa.targets=ds.sa.trialinfo(:,1); % 6 categories
% <@@<

% set the chunks (independent measurements)
% all trials are here considered to be independent
% set the chunks in ds.sa.chunks (independent measurements)
% all trials are here considered to be independent, so the chunks
% must all have a different value
% >@@>
nsamples=size(ds.samples,1);
ds.sa.chunks=(1:nsamples)';
% <@@<

% in addition give a label to each trial
index2label={'body','car','face','flower','insect','scene'};

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