Heuristics for Multiple Class Classification Problems via ROC hypersurface

机译：通过ROC Hyscransface对多级分类问题的启发式问题

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Receiver operating characteristics (ROC) graphs are useful for organizing binary classifiers and visualizing their performance. But it doesn't work on the corresponding multi-class classifiers problem. We analyse a series of multi-class classifiers and present a new algorithm based on its ROC parameters in which the goal is to minimise the cost of Q(Q-1) misclassification. Empirical results suggest that our algorithm is more stable than the several existing popular methods.

机译：接收器操作特性（ROC）图对于组织二进制分类器并可视化其性能是有用的。但它不适用于相应的多级分类器问题。我们分析了一系列多级分类器，并呈现了一种基于其ROC参数的新算法，其中目标是最小化Q（Q-1）错误分类的成本。经验结果表明，我们的算法比几种现有流行方法更稳定。

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《International Conference on Information and Computing》|2010年||共4页
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Yan-Hong WANG; Xiang CHENG;
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中图分类 G20-53;
关键词
Receiver Operator Characteristic (ROC); Multi-class classification; Label ranking;

机译：接收器操作员特征（ROC）;多级分类;标签排名;

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Heuristics for Multiple Class Classification Problems via ROC hypersurface

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