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Ensemble of Classifiers with Modification of Confidence Values

机译:置信度值修改的分类器集合

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摘要

In the classification task, the ensemble of classifiers have attracted more and more attention in pattern recognition communities. Generally, ensemble methods have the potential to significantly improve the prediction base classifier which are included in the team. In this paper, we propose the algorithm which modifies the confidence values. This values are obtained as an outputs of the base classifiers. The experiment results based on thirteen data sets show that the proposed method is a promising method for the development of multiple classifiers systems. We compared the proposed method with other known ensemble of classifiers and with all base classifiers.
机译:在分类任务中,分类器的集合在模式识别社区中吸引了越来越多的关注。通常,集合方法具有显着改善团队中包含的预测基本分类器的可能性。在本文中,我们提出了修改置信度值的算法。获得该值作为基本分类器的输出。基于十三个数据集的实验结果表明,该方法是开发多分类器系统的有希望的方法。我们将所提出的方法与分类器的其他已知的集合和所有基本分类器进行比较。

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