• Title/Summary/Keyword: Decision Tree analysis

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Comparisons of the Accuracy of Classification Methods in Sasang Constitution Diagnosis with Pulse Waves (맥파를 이용한 사상체질의 진단에 있어서 분류방법에 따른 진단의 정확도 비교)

  • Shin, Sang-Hoon;Kim, Jong-Yeol
    • 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.

Mother's Perceived Infant Smartphone Over-immersion Prediction Model: Data Mining Decision Tree Analysis (어머니가 지각한 유아의 스마트폰 과의존 예측모형 탐색: 데이터마이닝 의사결정나무 분석 활용)

  • Jung, Ji-Sook;Oh, Jung-A
    • Journal of the Korea Convergence Society
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    • v.11 no.5
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    • pp.97-105
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    • 2020
  • This study was to identify the main predictors of smartphone overdependece of infants perceived by mothers and to provide basic data useful for education and practice. For this, data-mining decision tree analysis was performed using SPSS program, and the fianl 410 researches were used for analysis. The results. In the case of the whole infants, the most important predictor of smartphone dependence was father's leisure activity parenting participation. For boys, their father's leisure activity was the most dependent on their smartphone dependence. However, even if father's participation in leisure activities was high, smartphone overdependence increased again when mother's overprotection and permissive attitude were high. Finally, For girls, the most influential variable on smartphone dependence was warmth and encouragement among mothers' parenting attitudes.

Exploration of the Factors Determining Satisfaction in First Job of Graduates from Engineering College by Decision Tree Analysis (의사결정나무분석에 의한 공과대학 졸업생의 첫 일자리 만족도 결정요인 탐색)

  • Lee, Jiyeon;Lee, Yeongju
    • Journal of Engineering Education Research
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    • v.24 no.1
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    • pp.15-23
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    • 2021
  • The first job of university graduates is the beginning of career development, and it has a great influence on a personal life in the transition process of a labor market later. The study has compared and analyzed the effects of major variables (whether or not one participates in the career and employment programs, the satisfaction in the education infrastructure and curriculum) related to university education that determine the satisfaction in the first job of graduates from the entire university of 4-year general courses and the engineering college with experiences of having the first job. Through this, it is meaningful to make it possible for the design of university education related to career and employment tailored to the engineering college. The results of 2017 Graduate Occupational Mobility Survey were used as the data for analysis, which was analyzed by the decision tree analysis. As it was found that the most important factor determining the satisfaction in the first job was student welfare facilities for the entire graduates among education infrastructure and was major curriculum and its content among education curriculum for the graduates from the engineering college, it was analyzed that factors related to majors were more important compared to other majors in the engineering college. The customized major curriculum and content should be considered as a priority, taking into account of the demand of the industry for the successful settlement of graduates from the engineering college in a labor market.

Determinants of Satisfaction, Revisit Intention, and Recommendation Intention Using Decision Tree Analysis - Foreign Tourists Visiting Korea during the COVID-19 Pandemic - (의사결정나무분석을 활용한 방문 만족도, 재방문 의사, 타인 권유 의사 결정요인 분석 - 코로나19 상황에서의 한국 방문 외래관광객을 대상으로 -)

  • Won-Sik Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.3
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    • pp.129-136
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    • 2023
  • The study aims to examine the determinants that affect satisfaction, revisit intention, and recommendation intention with foreign tourists who visited Korea despite the threat of COVID-19. This study employs the survey data collected by the Korea Tourism Organization from 8,135 foreign tourists who visited Korea in 2020. As the survey data contains a mixture of continuous and categorical variables, decision tree analysis can ensure analytical validity for the research. According to the analytical results, the determinants affecting satisfaction are the purpose of the visit and acceptance of self-quarantine during their stay. The factors influencing revisit intention are the purpose of the visit, frequency of the visit, and acceptance of self-quarantine during their stay. The determinants affecting recommendation intention are the purpose of the visit, length of stay, and gender. Based on the results of this analysis, this study not only explains the relationship between these determinants and tourism satisfaction, revisit intention, and recommendation intention, but also suggests implications for revitalizing tourism activities.

Development and Application of a Severity-Adjusted LOS Model for Pneumonia, organism unspecified patients (상세불명 병원체 폐렴의 중증도 보정 재원일수 모형 개발 및 적용)

  • Park, Jongho;Youn, Kyungil
    • Korea Journal of Hospital Management
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    • v.19 no.4
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    • pp.21-33
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    • 2014
  • This study was conducted to propose an insight into the appropriateness of hospital length of stay(LOS) by developing a severity-adjusted LOS model for patients with pneumonia, organism unspecified. The pneumonia risk-adjustment model developed in this paper is based upon the 2006-2010 the Korean National Hospital Discharge in-depth Injury Survey. Decision tree analysis revealed that age, admission type, insurance type, and the presence of additional disorders(pleural effusion, respiratory failure, sepsis, congestive heart failure etc.) were major factors affecting the severity-adjusted model using the Clinical Classifications Software(CCS). Also there was a difference in LOS among the regional hospitals, especially the hospital LOS has not been efficiently managed in Gyeongsangbuk-do, Jeollanam-do, Jeollabuk-do, Daejeon, and Busan. To appropriately manage hospital LOS, reliable statistical information about severity-adjusted LOS should be generated on a national level to make sure that hospitals voluntarily reduce excessive LOS and manage main causes of delayed discharge.

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Who is 'Shy Nuclear'? (누가 'Shy Nuclear'인가?)

  • Roh, Seungkook
    • Proceedings of the Korea Technology Innovation Society Conference
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    • 2017.11a
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    • pp.1523-1529
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    • 2017
  • 신정부의 탈원전 정책에 의해 급속하게 원자력계를 둘러싼 환경이 변하고 있다. 지금까지의 정부가 추진해온 원자력 중심의 전원계획이 신재생에너지 확대를 위한 계획으로 변화되어 가고 있다. 그리고 이러한 정부 정책 추진의 중심에는 매우 높은 대통령 지지율이 기반이 되고 있다. 하지만 여러 여론 조사 결과를 살펴보면 대통령은 약 65% 내외의 지지를 기록함에도 불구하고 원자력 활용에 대해서는 찬반 의견이 매우 팽팽하다. 즉, 원자력에 대한 이슈가 최근 에너지, 경제 문제가 아닌 정치 이슈가 된 상황에서도 원자력에 대해 지지를 보여주는 집단이 존재한다는 것을 뜻한다. 하지만 원자력을 지지하는 일반인들이 정치권과 탈핵 시민단체에서 원자력 분야를 소위 '적폐'로 규정하고 '원자력 마피아'로 명명한 상태에서 원자력에 대해 드러내놓고 지지하는 것은 쉽지 않다. 따라서 본 연구는 우리나라의 어떠한 계층에서 원자력을 지지하는지, 즉 'Shy Nuclear'를 찾고 이 지지층들의 특징에 대해서 분석하였다. 지지층 분류를 위해서 머신러닝의 분류분석 기법인 Decision Tree Analysis(의사결정나무) 방법론을 활용하였다. 분석 결과 Shy Nuclear를 결정하는 주 요인은 거주지역으로 나타났다. 아울러 수도권에 거주하고 있는 사무/관리/전문직/퇴직자 집단이 가장 원자력에 높은 호감도(긍정 76.1%)를 보여주었다.

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A Study of Data Mining Methodology for Effective Analysis of False Alarm Event on Mechanical Security System (기계경비시스템 오경보 이벤트 분석을 위한 데이터마이닝 기법 연구)

  • Kim, Jong-Min;Choi, Kyong-Ho;Lee, Dong-Hwi
    • Convergence Security Journal
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    • v.12 no.2
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    • pp.61-70
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    • 2012
  • The objective of this study is to achieve the most optimal data mining for effective analysis of false alarm event on mechanical security system. To perform this, this study searches the cause of false alarm and suggests the data conversion and analysis methods to apply to several algorithm of WEKA, which is a data mining program, based on statistical data for the number of case on movement by false alarm, false alarm rate and cause of false alarm. Analysis methods are used to estimate false alarm and set more effective reaction for false alarm by applying several algorithm. To use the suitable data for effective analysis of false alarm event on mechanical security analysis this study uses Decision Tree, Naive Bayes, BayesNet Apriori and J48Tree algorithm, and applies the algorithm by deducting the highest value.

FTA Modeling of Water Supply System for Hydro-power Plant (수력발전소 물 공급 설비에 대한 FTA 모형)

  • Jeon, Tae-Bo;Kwon, Chang-Seob
    • Journal of Industrial Technology
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    • v.26 no.B
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    • pp.145-155
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    • 2006
  • High level of reliability in facility operation is specifically required these days. The goal of this study is to secure a methodology for reliability analysis of hydro-power plant so that an appropriate decision for operation and investment can be made. Fault tree analysis of water supply system within hydro-power plant has been performed in this study. We briefly examined the electric power generation facility and water supply system. We then developed fault tree for the water supply system based on failure modes and effects analysis. We conclude this study and provided future research areas.

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