Known bugs

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While we always try to test each release as much as we can, inevitably some bugs will always slip through unnoticed. This page only shows the most important bugs that have surfaced after the release was made.

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If you happen to encounter something not listed here, please report it.

Version 6.2

Bug There is a small error in LRMMeasure that slows the modeling process if LRM is used together with another measure.
Status Fixed in next version
Workaround In src/matlab/measures/@LRMMeasure/calculateMeasure.m, replace line 204 by:
dtot(:,k) = (sum(d,1) ./ numTp) + dtot(:,k);

Version 6.1.1

Bug When modeling complex data, depending on the measure/error function used, the model generation process my be sub-optimal in some cases
Status Fixed in next version
Workaround Execute the error function you use (default = beeq) with a couple of complex numbers. The result must be a real number (non-complex). If this is not the case, fix the function (or ask us to send you a new one) or use a different function (also make sure to test it).

Version 6.1

Bug When using the LS-SVM models and you have not compiled the mex files the toolbox crashes with "Too many open files".
Status Fixed in next version
Workaround In /src/matlab/contrib/LS-SVMlab/trainlssvm.m replace on line 259 the text
with the text

Bug The ParetoModelBuilder can crash with "unknown function createModelFromIndividual()".
Status Fixed in next version
Workaround Replace the offending line (line 70 in modelbuilders/@ParetoModelbuilder/runLoop.m) with: "model = createModel(getModelFactory(s), populationEntry);". Make also sure that you have set the option paretoMode="true".

Bug When building models multi-objectively the toolbox uses a lot of diskspace and signals a lot of new best models
Status Fixed in next version
Workaround Remove in modelbuilders/@AdaptiveModelbuilder/private/orderBestModels.m, the condition "length(s.bestModels) == 1" so the if looks like "if ( oldBestModelId ~= newBestModelId )"