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Stacking Strong Ensembles of Classifiers

机译:堆叠强大的分类器集合

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摘要

A variety of methods have been developed in order to tackle a classification problem in the field of decision support systems. A hybrid prediction scheme which combines several classifiers, rather than selecting a single robust method, is a good alternative solution. In order to address this issue, we have provided an ensemble of classifiers to create a hybrid decision support system. This method based on stacking variant methodology that combines strong ensembles to make predictions. The presented hybrid method has been compared with other known-ensembles. The experiments conducted on several standard benchmark datasets showed that the proposed scheme gives promising results in terms of accuracy in most of the cases.
机译:为了解决决策支持系统领域中的分类问题,已经开发了多种方法。结合了多个分类器而不是选择单个鲁棒方法的混合预测方案是一个很好的替代解决方案。为了解决此问题,我们提供了一系列分类器来创建混合决策支持系统。该方法基于结合了强大合奏进行预测的堆叠变体方法。提出的混合方法已经与其他已知的乐团进行了比较。在几个标准基准数据集上进行的实验表明,在大多数情况下,提出的方案在准确性方面都给出了令人鼓舞的结果。

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