Dear Yann,
Thanks this should certainly help. I missed that on your blog.
Dear Rapten,
I'll try to explain it with a very concrete example.
Imagine the
target class label is set as OVTK_StimulationId_Label_01 and the
non target class label as OVTK_StimulationId_Label_02. Imagine you have two inputs in the voting classifier, connected to the outputs of two classifier processors. If the first classifier processor classifies the label as OVTK_StimulationId_Label_01 then the first input of the voting classifier will get one vote. If the second classifier processor does not output OVTK_StimulationId_Label_01 but another label it won't get a vote. If the second classifier does output the label OVTK_StimulationId_Label_01 then the second input of the voting classifier will also get a vote and there will be an ex-aequo. For this reason you can also set a
number of repetitions. The previous steps are then simply repeated and the input with the most votes will win. The voting classifier then outputs a label depending on the setting
Result class label base If this is OVTK_StimulationId_Label_01, then it will output OVTK_StimulationId_Label_01 if the first inputs wins, OVTK_StimulationId_Label_02 if the second one wins.
Concerning measuring accuracy, you could use the box
http://openvibe.inria.fr/documentation/ ... asure.html or the confusion matrix
http://openvibe.inria.fr/documentation/ ... atrix.html For a discussion on this topic:
viewtopic.php?f=13&t=442&hilit=multi+class
I hope this helps.
Best regards,
Dieter Devlaminck