TY  - RPRT
ID  - ba:gasiorowski
T1  - Examining Label Intersections in Pairwise Multilabel Classification
A1  - Gasiorowski, Tomasz
Y1  - 2015
M1  - Bachelorarbeit
T2  - TU Darmstadt, Knowledge Engineering Group
UR  - /lehre/arbeiten/bachelor/2015/Gasiorowski_Tomasz.pdf
N2  - Due to the overwhelming amount of data being processed nowadays, the importance of auto-
mated data classification is rising. Classifiers are relevant for many industries as they handle
topics such as medical image analysis, internet search queries and email spam filtering. Typical
tasks can be solved through multiclass classification, which involves assigning one of multiple
classes to an instance. A variant of the traditional multiclass classification problem is multil-
abel classification. In this setting, classes are not mutually exclusive and samples can belong
to multiple classes simultaneously. The dependencies between classes, particularly their over-
lapping areas, is the reason why this is a challenging problem. Classification through pairwise
decomposition is one of the leading methods for solving multilabel classification. In this method
we transform the multilabel problem into single-label problems through learning classifiers for
each pair of labels and combining their outputs to receive the end result. In this thesis we will
implement a modified pairwise decomposition method for multilabel classification and compare
its results to those of other approaches. We will also go deeper into the analysis of overlapping
areas and how this information can be used to make optimizations.
M1  - betreuer={ELM}
ER  -