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

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 the...

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Published inJournal of applied statistics Vol. 42; no. 8; pp. 1677 - 1689
Main Authors Sun, Meesun, Choi, Kwanghyun, Cho, Sungzoon
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 03.08.2015
Taylor & Francis Ltd
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ISSN0266-4763
1360-0532
DOI10.1080/02664763.2015.1005060

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Abstract 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.
AbstractList 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.
Author Cho, Sungzoon
Sun, Meesun
Choi, Kwanghyun
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SubjectTerms Adjustment
Algorithms
Armed forces
class imbalance
class overlap
Classification
Estimates
Inventories
mathematical programming-computational methods (90-08)
Military
Military Personality Inventory
Minorities
minority proportion
operations research
Personality
Personality traits
prevalence estimation
Psychological tests
ROC curve
statistics-applications (62Pxx)
statistics-data analysis (62-07)
Stockpiling
Studies
Title Estimating the minority class proportion with the ROC curve using Military Personality Inventory data of the ROK Armed Forces
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