• Journal of Digital Convergence
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• v.13 no.1
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• pp.353-366
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• 2015

The purpose of this study was to examine how region-specific characteristics affect the occurrence of cardiac arrest. To analyze, we combined a unique data set including key indicators of health condition and cardiac arrest occurrence at the 244 small administrative districts. Our data came from two main sources in Korea Center For Disease Control and Prevention (KCDC): 2010 Out-of-Hospital Cardiac Arrest Surveillance and Community Health Survey. We analyzed data by using multiple regression, geographically weighted regression and decision tree. Decision tree model is selected as the final model to explain regional variations of cardiac arrest. Factors of regional variations of cardiac arrest occurrence are population density, diagnosis rates of hypertension, stress level, participating screening level, high drinking rate, and smoking rate. Taken as a whole, accounting for geographical variations of health conditions, health behaviors and other socioeconomic factors are important when regionally customized health policy is implemented to decrease the cardiac arrest occurrence.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.171-172
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• 2013

우울은 군대 내 발생되는 극단적인 사고 중 하나인 자살의 주요 원인으로 제시되어 왔다. 본 연구는 군인들의 우울, 불안 및 자아존중감의 수준을 파악하고, 우울의 영향요인을 탐색하고 이들을 예측하는데 주로 사용해 왔던 다중회귀분석 방법과 효과적인 의사결정방법으로 알려진 회귀나무모형의 효과성을 비교해보고자 하였다. 방법: 횡단적 조사연구이며, 우울측정에는 CES-D, 불안측정은 SAI, 자아존중감은 Rosenberg(1965)의 도구를 사용하였다. 연구대상자는 강원도 전방 부대 근무 중인 군인이며, 534부가 회수되었다. SPSS/WIN 18.0을 이용하여 위계적 다중회귀분석과 회귀나무모형을 실시하였다. 결과: 대상자들의 우울, 불안 및 자아존중감의 정도는 각각 $10.7({\pm}9.8)$, $38.5({\pm}10.2)$과 $31.7({\pm}5.2)$이었다. 대상자의 23.6%(126명)가 경한 우울을 나타내었다. 다중회귀분석에 의한 우울 영향요인은 불안, 자아존중감과 복무기간이었으며, 우울에 대하여 62.0%의 설명력을 가지고 있었다. 또한 회귀나무모형에서는 높은 불안과 불안이 다소 낮더라도 전역 후 진로가 불확실한 집단이 우울 위험군일 것으로 예측되었다. 결론: 본 연구 대상자들의 우울의 주요 영향요인은 불안으로 나타났다. 군대 내에서 적용할 수 있는 불안 조절 방법 개발이 필요할 것으로 보인다. 또한 일부 요인에서 차이가 있어, 반복 연구가 필요하지만, 주요 변인인 불안을 예측했다는 점에서 보면 다중회귀분석과 회귀나무모형은 군인들의 우울을 예측에 유용한 방법으로 보인다.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.729-736
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• 2010

In this paper, we study the influence analysis of admission variables including their characteristics on academic achievements of freshmen at K university in Busan. First, multiple regression analysis is used to examine the main effects of admission variables including students' characteristics on the academic achievements. Also, Decision tree analysis is used to examine the interaction effects for the admission variables on the academic achievements. The results of this paper may be helpful to K university in designing effective admissions strategies for recruiting students.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.993-1003
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• 2012

The purpose of this study was to estimate the determinants of victory and defeat through analyzing records of Korean men pro-basketball. Statistical models of victory and defeat were established by collecting present basketball records (2010-2011, 2011-2012 season). Korea Basketball League (KBL) informs records of every pro-basketball game data. The six offence variables (2P%, 3P%, FT%, OR, AS, TO), and the four defense variables (DR, ST, GD, BS) were used in this study. PASW program was used for logistic regression and Answer Tree program was used for the decision tree. All significance levels were set at .05. Major results were as follows. In the logistic regression, 2P%, 3P%, and TO were three offense variables significantly affecting victory and defeat, and DR, ST, and BS were three significant defense variables. Offensive variables 2P%, 3P%, TO, and AS are used in constructing the decision tree. The highest percentage of victory was 80.85% when 2P% was in 51%-58%, 3P% was more than 31 percent, and TO was less than 11 times. In the decision tree of the defence variables, the highest percentage of victory was 94.12% when DR was more than 24, ST was more than six, and BS was more than two times.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.197-208
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• 2016

In this paper, data mining regression analysis and decision tree analysis techniques were used to analyze factors affecting the life satisfaction of middle school students. For this purpose, we analyzed Korean Children and Youth Panel Survey(KCYPS) data. As results, the common influencing factors to the life satisfaction were derived from regression analysis. Those factors are self-esteem, depression, total grade satisfaction, regional community awareness, career identity, annual delinquency damage experience, siblings' factors, trust, behavioral control, and concentration. Based on the result described by decision tree analysis, the factors that indicate a significant impact on the life satisfaction of middle school students were self-esteem, depression, career identity and attention factor.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.249-257
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• 2009

The purpose of this study is to find a classification method with high accuracy in regard with sasang constitutional diagnosis. The BMI, blood pressure, pulse wave, and Sasang constitution diagnosed by a specialist was collected from 2848 subjects who were apparently healthy. Through a selective procedure, the data of 1635 subjects was used in the analysis. The results with the classification methods such as the discriminant analysis, regression, decision tree and neural network were compared with the diagnosis of a Sasang constitutional specialist. In result, the discriminant analysis method was hard to qualify the assumption of the equality of covariance matrices within constitutional groups. Moreover, without BMI, the decision tree and neural network methods were very sensitive to the change of the analysis data. Therefore, the Logistic regression and the decision tree is recommended on condition that the decisive factors of constitution are well concerned.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.271-282
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• 2000

본 연구의 목적은 데이터마이닝 기법을 임상적으로 중요한 위치를 차지하고 있는 고혈압 환자의 특성과 치료에 따른 예후를 예측할 수 있는 지식을 발굴하고 이의 임상적용의 타당성을 검증하여 의사결정지원시스템을 개발하고 이의 유용성을 평가하는데 있다. 이에 연세대학교 의과대학 부속 세브란스 병원의 환자를 대상으로 로지스틱 회귀분석을 이용하여 혈압조절상의 위험요인의 규명하고, 의사결정나무분석을 통해 치료약제별 혈압조절군과 비조절군의 특성을 도출하고 각 대상군을 결정짓는 규칙을 생성하였으며, 이를 활용한 의사결정지원시스템의 개발 및c 평가를 시행하였다. 그 결과 기존 임상이론만을 활용한 시스템의 처방에 의한 혈압조절군보다 데이터마이닝 기법을 활용한 시스템의 처방에 의한 혈압조절군의 비율이 전체적으로 더 높게 나타남을 알 수 있었다. 본 연구의 결과는 우리나라 현실에 부합되는 고혈압 진료지침을 개발하고 적용, 평가하는데 기여할 수 있을 것으로 판단되며, 이와 같은 의사결정지원 시스템을 운영을 통해 실제 임상 진료에 적용해 봄으로써 그 효과와 실증적 가치를 창출할 수 있을 것이다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.559-564
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• 2021

The purpose of this study is to explore the factors that affect the intention to run remote classes after COVID-19 with university professors have fully experienced remote classes due to COVID-19. The research questions are what are the factors and the combinations of factors that affect the intention to run remote classes in the post-COVID-19. Data were collected through a survey of 311 remote classes at S Univ. in Seoul in fall 2020, and individuals and combinations of factors were confirmed through logistic regression analysis and decision tree analysis. As a result, individual factors were quality management, online office hours, quizzes midterm oral exams, video development, and student-student and instructor-student Q&A type between face-to-face and remote class. As combinations of factors, it was found that quality management×quiz×student Q&A and quality management×quiz×voting type had an effect on whether to run remote classes. Based on the results, we proposed to run and support remote classes in the post-COVID-19 era.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.419-429
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• 2015

We investigate how the regional prevalence of hyperlipidemia is affected by health-related and socioeconomic factors with a special emphasis on geographic variations. We focus on the likelihood of hyperlipidemia as function of various region-specific attributes. We analysis a data set at the level of 249 small administrative districts collected from 2012 Korean Community Health Survey by Korea Centers for Disease Control and Prevention. To estimate, we use several methods including correlation analysis, multiple regression and decision tree model. We find that the average prevalence of hyperlipidemia in 249 small districts is 9.6% and its coefficient of variation is 28.3%. Prevalence of hyperlipidemia in continental and capital regions is higher than in southeast coastal regions. Further findings using decision tree model suggest that variations of hyperlipidemia prevalence between regions is more likely to be associated with rate of employee, level of stress, prevalence of hypertension, angina pectoris, and osteoarthritis in their regions.

• 한국벤처창업학회:학술대회논문집
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• 2021.11a
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• pp.185-187
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• 2021

관리종목 지정 제도는 상장 기업 내 기업의 부실화를 경고하여 기업에게는 회생 기회를 주고, 투자자들에게는 투자 위험을 경고하기 위한 시장규제 제도이다. 본 연구는 관리종목과 비관리종목의 기업의 재무 데이터를 표본으로 하여 관리종목 지정 예측에 대한 연구를 진행하였다. 분석에 쓰인 분석 방법은 로지스틱 회귀분석, 의사결정나무, 서포트 벡터 머신, 소프트 보팅, 랜덤 포레스트, LightGBM이며 분류 정확도가 82.73%인 LightGBM이 가장 우수한 예측 모형이었으며 분류 정확도가 가장 낮은 예측 모형은 정확도가 71.94%인 의사결정나무였다. 대체적으로 앙상블을 이용한 학습 모형이 단일 학습 모형보다 예측 성능이 높았다.