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Today, High Performance Computing clusters (HPC) are an essential tool owing to they are an excellent platform for solving a wide range of problems through parallel and distributed applications. Nonetheless, HPC clusters consume large amounts of energy, which combined with notably increasing electricity prices are having an important economical impact, forcing owners to reduce operation costs. In...
Existing extensions of AdaBoost-based fuzzy rule learning to low quality databases yield suboptimal results in multi-class problems. A new procedure is proposed where the original multi-class database is transformed into several multi-label problems that can be tackled with binary AdaBoost. The performance of this proposal is assessed in comparison with other classification schemes for imprecise data...
Fuzzy set theory has been widely and successfully used as a mathematical tool to combine the outputs provided by the individual classifiers in a multiclassification system by means of a fuzzy aggregation operator. However, to the best of our knowledge, no fuzzy combination method has been proposed, which is composed of a fuzzy rule-based system. We think this can be a very promising research line...
When there is a substantial difference between the number of cases of the majority and minority classes, minimum error-based classification systems tend to overlook these last instances. This can be corrected either by preprocessing the dataset or by altering the objective function of the classifier. In this paper we analyze the first approach, in the context of genetic fuzzy systems (GFS), and in...
Many different fuzzy aggregation operators have been successfully used to combine the outputs provided by the individual classifiers in a multiclassification system. However, up to our knowledge, the use of fuzzy combination methods composed of a fuzzy system is less extended. By using a fuzzy linguistic rule-based classification system as a combination method, the resulting classifier ensemble would...
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