Abstract
The Multiple Classifier Systems are nowadays one of the most promising directions in pattern recognition. There are many methods of decision making by the group of classifiers. The most popular are methods that have their origin in vote methods, where the decision of the common classifier is a combination of simple classifiers decisions. On the other hand there exists a trend of combined classifiers, which are making their decisions basing on the discrimination function, this function is a combination of above-mentioned simple classifier functions. This work presents an attempt to estimate the classifier error, which bases on the combined discrimination function. Obtained from this estimation conclusions will serve to formulate project guidelines for this type of decision-making systems. At the end experimental results of combining algorithms are presented.
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Wozniak, M. (2008). Experiments on Linear Combiners. In: Pietka, E., Kawa, J. (eds) Information Technologies in Biomedicine. Advances in Soft Computing, vol 47. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68168-7_49
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DOI: https://doi.org/10.1007/978-3-540-68168-7_49
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