AbstractsComputer Science

Generalizing, Decoding, and Optimizing Support Vector Machine Classification

by Mario Michael Krell




Institution: Universit├Ąt Bremen
Department: FB3
Degree: PhD
Year: 2015
Record ID: 1100232
Full text PDF: http://elib.suub.uni-bremen.de/edocs/00104380-1.pdf


Abstract

The classification of complex data usually requires the composition of processing steps. Here, a major challenge is the selection of optimal algorithms for preprocessing and classification. Nowadays, parts of the optimization process are automized but expert knowledge and manual work are still required. We present three steps to face this process and ease the optimization. Namely, we take a theoretical view on classical classifiers, provide an approach to interpret the classifier together with the preprocessing, and integrate both into one framework which enables a semiautomatic optimization of the processing chain and which interfaces numerous algorithms.