While we saw there is a lot of research indirectly concerned with ensemble learn-ing schemes, only little research is directly related to investigating Stacking, the
most general such scheme. A stronger research focus { outside the scope of
this thesis { seems to be on simpler ensemble learning schemes such as Bagging
(Breiman, 1996) and AdaBoost (F reund & Schapire, 1996), which combine only a
single kind of classier. While we believe that the current v ariants StackingC and
sMM5 are very close to the optimum
3
, we hope that our comprehensive overview
on related research stimulates further work in ensemble learning and applying
ensembles in other research areas such as Game Playing, Self-Diagnosing Sys-tems and BioInformatics
While we saw there is a lot of research indirectly concerned with ensemble learn-ing schemes, only little research is directly related to investigating Stacking, themost general such scheme. A stronger research focus { outside the scope ofthis thesis { seems to be on simpler ensemble learning schemes such as Bagging(Breiman, 1996) and AdaBoost (F reund & Schapire, 1996), which combine only asingle kind of classi er. While we believe that the current v ariants StackingC andsMM5 are very close to the optimum3, we hope that our comprehensive overviewon related research stimulates further work in ensemble learning and applyingensembles in other research areas such as Game Playing, Self-Diagnosing Sys-tems and BioInformatics
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