In dynamic integration of classifiers each base classifier is given a weight proportional to its local accuracy with regard to the instance tested and the best base classifier is selected or the classifiers are integrated using weighted voting Our experiments with synthetic data sets simulating abrupt and gradual concept drifts and with a real world antibiotic resistance data set
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