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Estimating the minority class proportion with the ROC curve using Military Personality Inventory data of the ROK Armed Forces

机译:使用韩国武装部队的军事人格清单数据通过ROC曲线估算少数族裔比例

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摘要

The Republic of Korea Armed Forces includes maladjusted conscripts such as the mentally ill, the suicidal, the imprisoned, and those determined by the military commander to be maladjusted. To counteract these problems, it is necessary to identify the maladjusted conscripts to determine who among them would qualify for exemption from active military service or need special attention. We use the Military Personality Inventory (MPI) to make this prediction. Such a prediction presents a kind of class imbalance and class overlap problem, where the majority fulfil active service and the minority are maladjusted, the latter being discharged early from active service. Therefore, most classification algorithms are likely to show low classification performance. As an alternative, this study demonstrates the effective utilization of the receiver operating characteristics curve using MPI data to estimate the maladjusted proportion of persons sharing similar MPI test results. We confirm that the suggested method performs well using the real-world MPI data set. The suggested method is very useful to estimate the proportion of conscripts maladjusted to military life and can help in the management of such persons subject to conscription.
机译:大韩民国武装部队包括精神病患者,自杀者,被监禁者以及军事指挥官确定为精神失常者等失调的应征者。为了解决这些问题,有必要找出失职的应征者,以确定其中哪些人有资格免职现役或需要特别注意。我们使用军事人物清单(MPI)做出此预测。这样的预测提出了一种阶级失衡和阶级重叠的问题,其中多数人履行现役,而少数人则失职,后者早日退出现役。因此,大多数分类算法可能显示出较低的分类性能。作为替代方案,本研究证明了使用MPI数据有效利用接收器工作特性曲线来估计共享相似MPI测试结果的人员的失调比例。我们确认,建议的方法在实际MPI数据集上表现良好。所建议的方法对于估计应征入伍的军人生活中的比例非常有用,并且可以帮助管理应征入伍者。

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