Abstract
The article presents the concept of decomposition of the multidimensional classification task. The recognition procedure is divided into independent blocks. These blocks can be interpreted as lower classification problems. The structure of these blocks is presented as a decision tree. In this model the experts give the decision tree structure. The problem discussed in the work shows a selection of different classifiers (or their parameters) to the internal nodes of the decision tree. Experiments conducted for selected medical diagnosis problem show that the use of different classifiers can improve the quality of classification.
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Burduk, R., Zmyślony, M. (2012). Decomposition of Classification Task with Selection of Classifiers on the Medical Diagnosis Example. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28931-6_54
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DOI: https://doi.org/10.1007/978-3-642-28931-6_54
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