Designing Cost-Sensitive Ensemble – Genetic Approach
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The paper focuses on the problem of choosing classifiers for a committee of multiple classifier systems. We propose to design such an ensemble on the basis of an executing cost of elementary classifiers and additionally we fix mentioned above cost limit. Properties of the proposed approach were evaluated on the basis of computer experiments which were carried out on varied benchmark datasets. The results of experiments confirm that our proposition can be useful tool for designing cost-sensitive classifier committees.
KeywordsCost Limit Access Cost Neural Network Ensemble Pattern Recognition Task Majority Vote Rule
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