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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Comparing classifiers when the misallocation costs are uncertain
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Comparing classifiers when the misallocation costs are uncertain

机译:当分配错误的费用不确定时比较分类器

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摘要

Receiver Operating Characteristic (ROC) curves are popular ways of summarising the performance of two class classification rules. In fact, however, they are extremely inconvenient. If the relative severity of the two different kinds of misclassification is known, then an awkward projection operation is required to deduce the overall loss. At the other extreme, when the relative severity is unknown, the area under an ROC curve is often used as an index of performance. However, this essentially assumes that nothing whatsoever is known about the relative severity - a situation which is very rare in real problems. We present an alternative plot which is more revealing than an ROC plot and we describe a comparative index which allows one to take advantage of anything that may be known about the relative severity of the two kinds of misclassification.
机译:接收器工作特性(ROC)曲线是概括两个类别分类规则性能的常用方法。但是,实际上,它们非常不方便。如果已知两种不同类型错误分类的相对严重性,则需要笨拙的投影操作来推断总体损失。在另一个极端,当相对严重性未知时,ROC曲线下的面积通常用作性能指标。但是,这基本上是假设相对严重性一无所知-这种情况在实际问题中很少发生。我们提供了一种替代图,它比ROC图更具启发性,并且我们描述了一种比较指数,该指数允许人们利用有关两种错误分类的相对严重性的任何已知信息。

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