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Testing the difference between two Kolmogorov-Smirnov values in the context of receiver operating characteristic curves

机译:在接收器工作特性曲线的背景下测试两个Kolmogorov-Smirnov值之间的差异

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The maximum vertical distance between a receiver operating characteristic (ROC) curve and its chance diagonal is a common measure of effectiveness of the classifier that gives rise to this curve. This measure is known to be equivalent to a two-sample Kolmogorov-Smirnov statistic; so the absolute difference D between two such statistics is often used informally as a measure of difference between the corresponding classifiers. A significance test of D is of great practical interest, but the available Kolmogorov-Smirnov distribution theory precludes easy analytical construction of such a significance test. We, therefore, propose a Monte Carlo procedure for conducting the test, using the binormal model for the underlying ROC curves. We provide Splus/R routines for the computation, tabulate the results for a number of illustrative cases, apply the methods to some practical examples and discuss some implications.
机译:接收器工作特性(ROC)曲线与其机会对角线之间的最大垂直距离是产生该曲线的分类器有效性的常用度量。已知该度量等效于两个样本的Kolmogorov-Smirnov统计量。因此,通常会非正式地使用两个此类统计信息之间的绝对差D来衡量相应分类器之间的差异。 D的显着性检验具有重大的实践意义,但是可用的Kolmogorov-Smirnov分布理论排除了这种显着性检验的简单分析构造。因此,我们建议使用双标准模型作为基础ROC曲线来进行测试的蒙特卡洛程序。我们提供了Splus / R例程进行计算,将许多说明性情况的结果制成表格,将这些方法应用于一些实际示例,并讨论了一些含义。

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