Soft computing methods applied to combination of one-class classifiers
NeurocomputingPublished 3 August 2011
Tomasz Wilk, Michał Woźniak
Citations65
SJR quartileQ1
SJR score1.47
SNIP1.94
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TL;DR
The paper shows the possibilities of generalizing the two-class classification into multi- class classification by means of a fuzzy inference system and compares proposed combination methods with ECOC and two variations of decision templates, based on Euclidean and symmetric distance.
Abstract
The paper shows the possibilities of generalizing the two-class classification into multi-class classification by means of a fuzzy inference system. Fuzzy combiner harnesses the support values from classifiers to provide final response having no other restrictions on their structure. We compare proposed combination methods with ECOC and two variations of decision templates, based on Euclidean and symmetric distance. The effectiveness of the proposed combination method based on the fuzzy logic theory is also evaluated via computer experiments carried out on benchmark datasets.
Keywords
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