Treffer: Generalizing, Decoding, and Optimizing Support Vector Machine Classification ; Support Vector Machine Klassifikation Generalisieren, Dekodieren und Optimieren
Title:
Generalizing, Decoding, and Optimizing Support Vector Machine Classification ; Support Vector Machine Klassifikation Generalisieren, Dekodieren und Optimieren
Authors:
Contributors:
Kirchner, Frank, Büskens, Christof
Publisher Information:
Universität Bremen
Mathematik/Informatik (FB 03)
Mathematik/Informatik (FB 03)
Publication Year:
2015
Collection:
State and University Library Bremen: Electronic Library (E-LIB)
Subject Terms:
Time:
000
Document Type:
Dissertation
doctoral or postdoctoral thesis
File Description:
application/pdf
Language:
English
Availability:
Rights:
info:eu-repo/semantics/openAccess
Accession Number:
edsbas.7495DF15
Database:
BASE
Weitere Informationen
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.