• 제목/요약/키워드: CART 분석

검색결과 153건 처리시간 0.03초

Developing the Traffic Accident Prediction Model using Classification And Regression Tree Analysis (CART분석을 이용한 교통사고예측모형의 개발)

  • Lee, Jae-Myung;Kim, Tae-Ho;Lee, Yong-Taeck;Won, Jai-Mu
    • International Journal of Highway Engineering
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    • 제10권1호
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    • pp.31-39
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    • 2008
  • Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. The accurate traffic accident prediction model requires not only understanding of the factors that cause the accident but also having the transferability of the model. So, this paper suggest the traffic accident diagram using CART(Classification And Regression Tree) analysis, developed Model is compared with the existing accident prediction models in order to test the goodness of fit. The results of this study are summarized below. First, traffic accident prediction model using CART analysis is developed. Second, distance(D), pedestrian shoulder(m) and traffic volume among the geometrical factors are the most influential to the traffic accident. Third. CART analysis model show high predictability in comparative analysis between models. This study suggest the basic ideas to evaluate the investment priority for the road design and improvement projects of the traffic accident blackspots.

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Efficiency Analysis of Buyer-Carts for B2B EC (기업간 전자상거래를 위한 구매자쇼핑카트 효율성 분석)

  • Lim, Gyoo-Gun;Lee, Jae-Kyu
    • Journal of Information Technology Services
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    • 제1권1호
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    • pp.17-27
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    • 2002
  • Buyer-carts to support the purchasing process in the B2B EC platform, can be categorized as s-cart, i-cart, and b-cart depending upon its residing sites : seller, intermediary, and buyer sites. In this paper, after proposing the desired features of buyer-carts in B2B EC as identification, collection, trashing, ordering, payment, tracking, recording, purchasing decision support, and transmission of records to e-procurement systems, we try to analyze each buyer-cart qualitatively from such viewpoints. Moreover, we propose an efficiency evaluation model for quantitative analysis. By setting variables from interview of employees in 30 listed companies In Korea, we try to evaluate the efficiency of buyer-carts in B2B EC. From this paper, we show that the b-cart platform is more efficient than other buyer-carts especially in B2B EC.

On-line Reinforcement Learning for Cart-pole Balancing Problem (카트-폴 균형 문제를 위한 실시간 강화 학습)

  • Kim, Byung-Chun;Lee, Chang-Hoon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제10권4호
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    • pp.157-162
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    • 2010
  • The cart-pole balancing problem is a pseudo-standard benchmark problem from the field of control methods including genetic algorithms, artificial neural networks, and reinforcement learning. In this paper, we propose a novel approach by using online reinforcement learning(OREL) to solve this cart-pole balancing problem. The objective is to analyze the learning method of the OREL learning system in the cart-pole balancing problem. Through experiment, we can see that approximate faster the optimal value-function than Q-learning.

Quantitative Performance Analysis of Buyer-Carts in B2B EC: Buyer's Interactional Efforts Perspective (기업간 전자상거래에서의 구매자 쇼핑카트 정량적 성능분석: 구매자의 상호작용 노력 중심)

  • Lim, Gyoo-Gun;Lee, Jae-Kyu
    • Asia pacific journal of information systems
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    • 제14권1호
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    • pp.59-77
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    • 2004
  • Even though B2B EC is becoming popular, there have been not so much studies about performance evaluation methodology for B2B systems. In this paper, after analyzing buyer-carts systematically focusing on the buyer's interactional efforts on the typical buying processes of each buyer-cart, we propose a quantitative performance evaluation model. For this, we categorize buyer-carts in B2B EC as s-cart, i-cart, and b-cart depending upon its residing sites: seller, intermediary, and buyer sites. And after proposing the desired features of buyer-carts in B2B EC as identification, collection, trashing, ordering, payment, tracking, recording, purchasing decision support, and transmission of records to e-procurement systems, we derive a performance evaluation model by calculating detail sub-processes from the desired features' viewpoints. By setting variables from a survey on the actual condition of using buyer-carts in companies in Korea, we try to evaluate the performance of buyer-carts in B2B EC. In this paper, we suggest a new methodology of performance evaluation for B2B systems, and show that the b-cart platform is more efficient than other buyer-carts especially in B2B EC.

Prediction Model for Toothache Occurrence in College Students by using Oral Hygiene Habits and the CART Model (대학생의 구강건강관리실태와 CART모델을 이용한 치통발생예측)

  • Kim, Nam-Song;Lim, Kun-Ok
    • Journal of dental hygiene science
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    • 제9권4호
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    • pp.419-426
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    • 2009
  • The occurrence of toothache signals the malfunction in oral health, which allows the detection of any abnormal condition in the oral cavity at an early stage to prevent the condition from worsening, and thus can act as a preventive measure. This study has looked into the status of oral health management in relation to toothache through the structured survey administered to 235 college students. Based on the survey results, this study aimed at comparing the toothache occurrence prediction between regression analysis and CART model in order to clarify the relationship between the factors of oral health management habits that contribute to toothache occurrence. According to the result, there was a difference between the present health status and the health status of the past year depending on the presence or non-presence of toothache occurrence (p<0.05). There was a difference in the regularity of meal time depending on the presence non-presence of toothache occurrence from the dietary habits of the research subjects (p<0.05). As for the presence or non-presence of toothache occurrence from the oral hygiene habits of the research subject, there was a difference between the occurrence and nonoccurrence of bleeding during brushing or flossing (p<0.05). According to the results of regression analysis, no factors were signifiant in the relationship with the presence or non-presence of toothache occurrence from the status of life habits and oral hygiene habits. 70% of the researched group was randomly selected as the sample for generating an analytical model and the remaining 30% was used as the sample for generating an evaluation model. According to the results of CART model, the occurrence of toothache was higher in the case of irregular meal time and poor current health condition than the case of average or satisfactory health condition. The above results imply that CART model is very useful technique in predicting toothache occurrence compared to regression analysis, and suggests that CART model could be very useful in predicting other oral diseases including toothache.

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The Prediction Performance of the CART Using Bank and Insurance Company Data (CART의 예측 성능:은행 및 보험 회사 데이터 사용)

  • Park, Jeong-Seon
    • The Transactions of the Korea Information Processing Society
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    • 제3권6호
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    • pp.1468-1472
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    • 1996
  • In this study, the performance of the CART(Classification and Regression Tree) is compared with that of discriminant analysis method. In most experiments using bank data, discriminant analysis shows better performance in terms of the total cost. In contrast, most experiments using insurance data show that the CART is better than discriminant analysis in terms of the total cost. The contradictory result are analysed by using the characteristics of the data sets. The performances of both the Classification and Regression Tree and discriminant analysis depend on the parameters:failure prior probability, data used, type I error, type II error cost, and validation method.

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A Study of The Determinants of Turnover Intention and Organizational Commitment by Data Mining (데이터마이닝을 활용한 이직의도와 조직몰입의 결정요인에 대한 연구)

  • Choi, Young Joon;Shim, Won Shul;Baek, Seung Hyun
    • Journal of the Korea Society for Simulation
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    • 제23권1호
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    • pp.21-31
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    • 2014
  • In this article, data mining simulation is applied to find a proper approach and results of analysis for study of variables related to organization. Also, turnover intention and organizational commitment are used as target (dependent) variables in this simulation. Classification and regression tree (CART) with ensemble methods are used in this study for simulation. Human capital corporate panel data of Korea Research Institute for Vocation Education & Training (KRIVET) is used. The panel data is collected in 2005, 2007, and 2009. Organizational commitment variables are analyzed with combined measure variables which are created after investigation of reliability and single dimensionality for multiple-item measurement details. The results of this study are as follows. First, major determinants of turnover intention are trust, communication, and talent management-oriented trend. Second, the main determining factors for organizational commitment are trust, the number of years worked, innovation, communication. CART with ensemble methods has two ensemble CART methods which are CART with Bagging and CART with Arcing. Comparing two methods, CART with Arcing (Arc-x4) extracted scenarios with very high coefficients of determination. In this study, a scenario with maximum coefficient of determinant and minimum error is obtained and practical implications are presented. Using one of data mining methods, CART with ensemble method. Also, the limitation and future research are discussed.

Efficiency Analysis of Buyer-Carts for B2B EC (기업간 전자상거래를 위한 구매자쇼핑카트 효율성 분석)

  • Lim, Gyoo-Gun
    • 한국IT서비스학회:학술대회논문집
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    • 한국IT서비스학회 2002년도 창립기념 학술대회
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    • pp.249-257
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    • 2002
  • B2B EC 플랫폼에서의 구매 프로세스를 지원하기 위한 구매자 쇼핑카트는 위치에 따라 판매자쪽의 s-cart, 중개자쪽의 i-cart, 구매자쪽의 b-cart로 분류할 수 있다. 본 논문에서는 B2B EC에서의 구매자 쇼핑카트의 요구기능을 사용자 식별, 상품정보수집, 물품정보제거, 주문처리, 지불처리, 진행사항 추적, 구매기록, 구매의사결정지원, 전자구매시스템에 구매기록 전송 등 9 가지로 제시하고, 이러한 관점에서 각 구매자 쇼핑카트에 대한 정성적인 비교 분석을 시도한다. 그리고 효율평가모델 제시를 통한 정량적인 분석과 상장기업 30개사의 구매직원에 대한 인터뷰를 통한 변수값 설정을 통해서 B2B EC환경에서의 구매자 쇼핑카트의 효율성 평가를 시도한다. 본 논문을 통해서 B2B EC환경에서는 b-cart 방식의 구매자쇼핑카트 방법이 효율적인 플랫폼임을 제시한다.

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Power of Expanded Multifactor Dimensionality Reduction with CART Algorithm (CART 알고리즘을 활용한 확장된 다중인자 차원축소방법의 검정력 평가)

  • Lee, Jea-Young;Lee, Jong-Hyeong;Lee, Ho-Guen
    • Communications for Statistical Applications and Methods
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    • 제17권5호
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    • pp.667-678
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    • 2010
  • It is important to detect the gene-gene interaction in GWAS(Genome-Wide Association Study). There are many studies about detecting gene-gene interaction. The one is Multifactor dimensionality reduction method. But MDR method is not applied continuous data and expanded multifactor dimensionality reduction(E-MDR) method is suggested. The goal of this study is to evaluate the power of E-MDR for identifying gene-gene interaction by simulation. Also we applied the method on the identify interaction e ects of single nucleotid polymorphisms(SNPs) responsible for economic traits in a Korean cattle population (real data).

Effective Diagnostic Method Of Breast Cancer Data Using Decision Tree (Decision Tree를 이용한 효과적인 유방암 진단)

  • Jung, Yong-Gyu;Lee, Seung-Ho;Sung, Ho-Joong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • 제10권5호
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    • pp.57-62
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    • 2010
  • Recently, decision tree techniques have been studied in terms of quick searching and extracting of massive data in medical fields. Although many different techniques have been developed such as CART, C4.5 and CHAID which are belong to a pie in Clermont decision tree classification algorithm, those methods can jeopardize remained data by the binary method during procedures. In brief, C4.5 method composes a decision tree by entropy levels. In contrast, CART method does by entropy matrix in categorical or continuous data. Therefore, we compared C4.5 and CART methods which were belong to a same pie using breast cancer data to evaluate their performance respectively. To convince data accuracy, we performed cross-validation of results in this paper.