The use of probability density functions to improve the interpretation of FSV results

Zhang Gang, A. Duffy, H. Sasse, W. Lixin
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引用次数: 9

Abstract

This paper presents research undertaken using a continuous probability density function as a supplement to the confidence histograms in Feature Selective Validation. Such an approach shares the benefits of `categorisation' from a humanuser perspective but, because of the continuous nature of the distribution, it also allows further inter-comparison analysis to be undertaken such as using non-parametric tests on the distributions. This approach improves the analysis of FSV data when multiple comparisons are required to be performed.
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利用概率密度函数改进FSV结果的解释
本文介绍了在特征选择验证中使用连续概率密度函数作为置信度直方图的补充进行的研究。从人类用户的角度来看,这种方法具有“分类”的好处,但由于分布的连续性,它还允许进行进一步的相互比较分析,例如对分布使用非参数测试。当需要执行多次比较时,这种方法改进了FSV数据的分析。
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