Difference between revisions of "Known bugs"
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If you happen to encounter something not listed here, please [[reporting problems|report it]]. | If you happen to encounter something not listed here, please [[reporting problems|report it]]. | ||
| + | |||
| + | == Version 6.2 == | ||
| + | |||
| + | |||
| + | {| border="0" style="text-align:left" | ||
| + | |- | ||
| + | !'''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: <source lang="matlab">dtot(:,k) = (sum(d,1) ./ numTp) + dtot(:,k);</source> | ||
| + | |- | ||
| + | |} | ||
| + | |||
| + | |||
| + | == Version 6.1.1 == | ||
| + | |||
| + | |||
| + | {| border="0" style="text-align:left" | ||
| + | |- | ||
| + | !'''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 == | == Version 6.1 == | ||
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|- | |- | ||
!'''Workaround''' | !'''Workaround''' | ||
| − | | In /src/matlab/contrib/LS-SVMlab/trainlssvm.m replace on line 259 the text < | + | | In /src/matlab/contrib/LS-SVMlab/trainlssvm.m replace on line 259 the text <source lang="bash">'model.implementation=''CFILE''</source> with the text <source lang="bash">'model.implementation=''MATLAB''</source> |
|- | |- | ||
|} | |} | ||
| + | |||
| + | |||
{| border="0" style="text-align:left" | {| border="0" style="text-align:left" | ||
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|- | |- | ||
!'''Workaround''' | !'''Workaround''' | ||
| − | | Replace the offending line (line 70 in runLoop.m) with: "model = createModel(getModelFactory(s), populationEntry);". Make also sure that you have set the option ''paretoMode="true"''. | + | | 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"''. |
|- | |- | ||
|} | |} | ||
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|- | |- | ||
!'''Workaround''' | !'''Workaround''' | ||
| − | | Remove in modelbuilders/@AdaptiveModelbuilder/private/orderBestModels.m, | + | | Remove in modelbuilders/@AdaptiveModelbuilder/private/orderBestModels.m, the condition "length(s.bestModels) == 1" so the if looks like "if ( oldBestModelId ~= newBestModelId )" |
|- | |- | ||
|} | |} | ||
Latest revision as of 13:25, 8 October 2009
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.
To stay up to date with the latest news and releases, we also recommend subscribing to our newsletter here. Traffic will be kept to a minimum and you can unsubscribe at any time.
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 'model.implementation=''CFILE''
'model.implementation=''MATLAB''
|
| 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 )" |
