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Pattern recognition of the polygraph using fuzzy classification

机译:基于模糊分类的测谎仪模式识别

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摘要

Polygraph tests are a widely used method to distinguish between truth and deception. Polygraph charts are usually analyzed by human interpreters. However, computer algorithms are now being developed to score the tests or verify the results. These methods are based on statistical classification techniques. In this study a number of time, frequency and correlation domain features were selected and used. The fuzzy K-nearest neighbor algorithm was used to classify the polygraph charts; a correct classification of ninety-one percent was obtained for a set of one hundred case files supplied by the NSA.
机译:测谎仪测试是一种用于区分真相和欺骗的广泛使用的方法。测谎仪图表通常由人工翻译进行分析。但是,现在正在开发计算机算法来对测试进行评分或验证结果。这些方法基于统计分类技术。在这项研究中,选择并使用了许多时间,频率和相关域特征。采用模糊K最近邻算法对测谎仪图进行分类。对于国家安全局提供的一组一百份案卷,正确分类为百分之九十一。

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