Die druckbare Version wird nicht mehr unterstützt und kann Darstellungsfehler aufweisen. Bitte aktualisiere deine Browser-Lesezeichen und verwende stattdessen die Standard-Druckfunktion des Browsers.
Vortragende(r)
|
Alexander Poth
|
Vortragstyp
|
Bachelorarbeit
|
Betreuer(in)
|
Edouard Fouché
|
Termin
|
Fr 14. Dezember 2018
|
Vortragsmodus
|
|
Kurzfassung
|
The evaluation of data stream mining algorithms is an important task in current research. The lack of a ground truth data corpus that covers a large number of desireable features (especially concept drift and outlier placement) is the reason why researchers resort to producing their own synthetic data. This thesis proposes a novel framework ("streamgenerator") that allows to create data streams with finely controlled characteristics. The focus of this work is the conceptualization of the framework, however a prototypical implementation is provided as well. We evaluate the framework by testing our data streams against state-of-the-art dependency measures and outlier detection algorithms.
|