• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.453-470
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• 1995

We describe a constrained optimal classification rule for the case when the prior probability of an observation belonging to one of the two populations is unknown. This is done by suggesting a balanced design for the classification experiment and constructing the optimal rule under the balanced design condition. The rule si characterized by a constrained minimization of total risk of misclassification; the constraint of the rule is constructed by the process of equation between Kullback-Leibler's directed divergence measures obtained from the two population conditional densities. The efficacy of the suggested rule is examined through two-group normal classification. This indicates that, in case little is known about the relative population sizes, dramatic gains in accuracy of classification result can be achieved.

• 산경연구논집
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• 제13권10호
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• 한국안전학회지
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• 제33권6호
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• pp.128-135
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• 2018

Currently, the government selects products that are likely to cause harm to consumers as safety management targets and classifies them into three types: safety certification, safety confirmation, and supplier conformity verification. In addition, the government conducts safety surveys on products in circulation or accident products, and recalls products that are of great concern to consumer risks. In this paper, we have developed RAP (Risk Assessment method based on Probability), which is a probability based product risk assessment method, for the classification of safety management type of product and safety investigation, and have shown an application example. In this process, information is used for the CISS (Consumer Injury Surveillance System) of the Korean Consumer Agency. In addition, we apply the cluster analysis to classify the current supervised children products into three groups. Then, we confirm the effectiveness of RAP by comparing the result of RAP application, cluster analysis result and current safety management classification type. Also, we recognize the need to review the current safety management classification criteria for classifying products into three types.

• 한국생활과학회지
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• 제21권6호
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• pp.1129-1144
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• 2012

The purpose of this study was to investigate the gender difference in adolescent's problem behavior and depression, and The main aim of this study was to develop a fundamental web design to provide information content that would be easy for average consumers to understand based on the classification of information related to food safety. Based on the information obtained through in-depth interviews, the researchers developed an information classification system that meets the needs of consumers, and which serve as a basic framework for a homepage for a food safety information center. A total of 62 food items in 6 areas were selected based on reports of food safety related events occurring between 1998-2009 (KFDA 2008). The classification system of risk factors such as chemical risk factors and biological risk factors were categorized. The specific features of the information content for individual food items provided for classification based on evaluation by professional food scientists and the importance of risk factors. By providing a consumer participation section and company participation section, it was anticipated that the food safety information center would be able to act as a moderator for food safety information communication among consumers, the food industry, and the government. Based on the development of a classification system and framework, a design plan and tree-map for the internet site was developed.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2003년도 학술대회지
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• pp.217-221
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• 2003

본 연구에서는 공동주택공사에서 발생하는 공기지연 리스크에 대한 분류체계와 분석방법을 제안하였다. 서울${\cdot}$경기 지역과 부산${\cdot}$경남 지역의 공동주택공사 현장을 중심으로 실무자 면담 및 설문조사를 실시하였고, 그 결과를 바탕으로 주요 광종 분류와 각 공종의 공기지연 리스크 수준과 지수를 산정하였다. 본 연구는 공동주택공사의 주요 공종인 토공사, 골조공사, 조적${\cdot}$미장공사, 창호${\cdot}$유리공사, 수장공사의 공기지연 리스크 요인의 리스크 수준, 지수 그리고 순위를 분석하여 공기지연 리스크 관리 시스템 구축을 위한 기초적인 자료를 제시하는 것을 목적으로 하였다.

• Safety and Health at Work
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• 제14권3호
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• pp.272-278
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• 2023

Background: Some working conditions may pose a higher physical or psychological demand to pregnant women leading to increased risks of pregnancy complications. Objectives: We assessed the association of woman's employment status and the industrial classification with obstetric complications. Methods: We conducted a national population study using the National Health Information Service database of Republic of Korea. Our analysis encompassed 1,316,310 women who experienced first-order live births in 2010-2019. We collected data on the employment status and the industrial classification of women, as well as their diagnoses of preeclampsia (PE) and gestational diabetes mellitus (GDM) classified as A1 (well controlled by diet) or A2 (requiring medication). We calculated odds ratios (aORs) of complications per employment, and each industrial classification was adjusted for individual risk factors. Results: Most (64.7%) were in employment during pregnancy. Manufacturing (16.4%) and the health and social (16.2%) work represented the most prevalent industries. The health and social work exhibited a higher risk of PE (aOR = 1.11, 95% confidence interval [CI]: 1.03-1.21), while the manufacturing industry demonstrated a higher risk of class A2 GDM (1.20, 95% CI: 1.03-1.41) than financial intermediation. When analyzing both classes of GDM, women who worked in public administration and defense/social security showed higher risk of class A1 GDM (1.04, 95% CI: 1.01, 1.07). When comparing high-risk industries with nonemployment, the health and social work showed a comparable risk of PE (1.02, 95% CI: 0.97, 1.07). Conclusion: Employment was associated with overall lower risks of obstetric complications. Health and social service work can counteract the healthy worker effect in relation to PE. This highlights the importance of further elucidating specific occupational risk factors within the high-risk industries.

• Industrial Engineering and Management Systems
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• 제13권4호
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• pp.449-453
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• 2014

Chronic diseases including hypertension and its complications are major sources causing the national medical expenditures to increase. We aim to predict the risk of hypertension complications for hypertension patients, using the sample national healthcare database established by Korean National Health Insurance Corporation. We apply classification techniques, such as logistic regression, linear discriminant analysis, and classification and regression tree to predict the hypertension complication onset event for each patient. The performance of these three methods is compared in terms of accuracy, sensitivity and specificity. The result shows that these methods seem to perform similarly although the logistic regression performs marginally better than the others.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2004년도 추계 학술발표회 제16권2호
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• pp.663-666
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• 2004

An analysis of the annual frequency of collapse(AF) is performed for each bridge pier exposed to ship collision. AF is computed for each bridge component and vessel classification. The summation of AFs computed over all of the vessel classification intervals for a specific component should equal the annual frequency of collapse of the component. The designer should use judgment in developing a distribution of the vessel frequency data based on discrete groupings or categories of vessel size by DWT. In the present study the effect of vessel classification on the annual frequency of collapse in the ship collision risk assessment is investigated by illustrative numerical examples based on the vessel frequency data of the domestic harbor. The DWT interval for larger vessels has more effect on the ship collision risk. Therefore the expert judgement in determining the larger DWT interval is required because the design impact lateral resistances of bridge components depend on the ship collision risk.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.371-374
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• 2007

For development of landslide risk assessment techniques using GIS(Geographic Information System), this study classifies the category of socioeconomic factors. The landslide quantitative risk assessment performs first prediction of flow trajectory and runout distance of debris flow over natural terrain. Based on those results, it can be analyzed the factors of socioeconomic which are directly related to the magnitude of risk due to landslide hazards. Those risk assessment results can deliver factual damage situation prediction to policy making for the landslide damage mitigation. Therefore, this study is based on feature classification of the digital map ver. 2.0 provided by the National Geographic Information Institute. The category of factors can be used as useful data in preventing landslide.

• Genomics & Informatics
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• 제1권2호
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• pp.80-86
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• 2003

Human Papillomavirus (HPV) infection is known as the main factor for cervical cancer which is a leading cause of cancer deaths in women worldwide. Because there are more than 100 types in HPV, it is critical to discriminate the HPVs related with cervical cancer from those not related with it. In this paper, the risk type of HPVs using their textual explanation. The important issue in this problem is to distinguish false negatives from false positives. That is, we must find high-risk HPVs as many as possible though we may miss some low-risk HPVs. For this purpose, the AdaCost, a cost-sensitive learner is adopted to consider different costs between training examples. The experimental results on the HPV sequence database show that the consideration of costs gives higher performance. The improvement in F-score is higher than that of the accuracy, which implies that the number of high-risk HPVs found is increased.