• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.489-503
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• 2000

Data mining means data analysis and model selection using various types of data in order to explore useful information and knowledge for making decisions. Examples of data mining include scoring for credit analysis of a new customer and scoring for churn management, where the customers with high scores are given special attention. In this paper, scoring is interpreted as a modeling process of the conditional probability and polyclass scoring method is described. German credit data, a PC communication company data and a mobile communication company data are used to compare the performance of polyclass scoring method with that of the scoring method based on a tree model.

• Korean Journal of Otorhinolaryngology-Head and Neck Surgery
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• v.61 no.11
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• pp.593-599
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• 2018

Background and Objectives Respiratory scoring guidelines for children and adults have been used for evaluating adolescents both in the 2007 and 2012 American Academy of Sleep Medicine (AASM) scoring manuals. We compared the scoring methods of polysomnography used in these scoring manuals, where pediatric and adult scoring rules were adopted for the diagnosis of sleep apnea in adolescents. Subjects and Method 106 Korean subjects aged between 13 and 18 years were enrolled. All subjects underwent overnight polysomnography in a sleep laboratory. Data were scored according to both pediatric and adult guidelines in the 2007 and 2012 AASM scoring manuals. Results Both pediatric and adult apnea hypopnea index (AHI) using the 2012 method were significantly higher than those using the 2007 method. The difference in AHI compared between pediatric and adult scores with the 2012 AASM scoring system was markedly decreased from that with the 2007 method. There was a significant discordance in sleep apnea diagnosis between pediatric and adult scoring rules in the 2012 method. Conclusion Both pediatric and adult rules were used for the diagnosis of adolescent sleep apnea in the 2012 method. However, there was significant discordance in the diagnosis between pediatric and adult scoring guidelines in the 2012 AASM manual, probably due to different cut-off values of AHI for the diagnosis of sleep apnea in pediatric (${\geq}1$) and adult (${\geq}5$) patients. Further studies are needed to determine a more reasonable cut-off value for the diagnosis of sleep apnea in adolescents.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.521-532
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• 2005

In the current College Scholastic Aptitude Test (CSAT), the standardized scoring system is being adopted to adjust te differences of degrees of difficulty between the optional subjects. But it becomes clear that the system has several weak points, some of which are considered to be very serious. In this paper we propose an alternative method, so-called the additive scoring system. It determines the additional points per each subjects, according to the subject mean scores. The proposed method has been simulated using the data of 2005' CSAT, and it turns out that the additive scoring system reduces or remove the troubles caused by the standardized scoring system.

• BMB Reports
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• v.35 no.5
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• pp.513-517
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• 2002

We describe a new method for identifying the sequences that signal the start of translation, and the boundaries between exons and introns (donor and acceptor sites) in human mRNA. According to the mandatory keyword, ORGANISM, and feature key, CDS, a large set of standard data for each signal site was extracted from the ASCII flat file, gbpri.seq, in the GenBank release 108.0. This was used to generate the scoring matrices, which summarize the sequence information for each signal site. The scoring matrices take into account the independent nucleotide frequencies between adjacent bases in each position within the signal site regions, and the relative weight on each nucleotide in proportion to their probabilities in the known signal sites. Using a scoring scheme that is based on the nucleotide scoring matrices, the method has great sensitivity and specificity when used to locate signals in uncharacterized human genomic DNA. These matrices are especially effective at distinguishing true and false sites.

• Journal of Industrial Convergence
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• v.16 no.4
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• pp.33-46
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• 2018

Personal credit scoring is an effective tool for banks to properly guide decision profitably on granting loans. Recently, many classification algorithms and models are used in personal credit scoring. Personal credit scoring technology is usually divided into statistical method and non-statistical method. Statistical method includes linear regression, discriminate analysis, logistic regression, and decision tree, etc. Non-statistical method includes linear programming, neural network, genetic algorithm and support vector machine, etc. But for the development of the credit scoring model, there is no consistent conclusion to be drawn regarding which method is the best. In this paper, we will compare the performance of the most common scoring techniques such as logistic regression, neural network, and support vector machines using personal credit data of the financial institution in China. Specifically, we build three models respectively, classify the customers and compare analysis results. According to the results, support vector machine has better performance than logistic regression and neural networks.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.436-442
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• 2005

The purpose of this study is to develop indices and a scoring method for effectively evaluating the project of rural well-longevity villages which makes up for insufficient parts of existing projects on improving settlement foundation and production environment. Evaluating indices include qualitative factors originated from the characteristics of the project so a scoring method based on an information measure technique is used for evaluating the results from each village. Evaluating indices are provided differently depending on each purpose for evaluation. Result indices can be used for ranking project villages and fundamental indices can be used to analyze villages elaborately to improve project plans.

• Journal of the Korea Society of Computer and Information
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• v.18 no.8
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• pp.17-25
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• 2013

TIn this paper, we propose a model automatically scoring a student's answer for a descriptive problem by using a voting method. Considering the model construction cost, the proposed model does not separately construct the automatic scoring model per problem type. In order to utilize features useful for automatically scoring the descriptive answers, the proposed model extracts feature values from the results, generated by comparing the student's answer with the answer sheet. For the purpose of improving the precision of the scoring result, the proposed model collects the scoring results classified by a few machine learning based classifiers, and unanimously selects the scoring result as the final result. Experimental results show that the single machine learning based classifier C4.5 takes 83.00% on precision while the proposed model improve the precision up to 90.57% by using three machine learning based classifiers C4.5, ME, and SVM.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.169-175
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• 2011

In this paper, an automatic scoring system of the OMR answer sheet is implemented using Gray Scale and image segmentation method. The proposed method was used to extract the OMR data on multiple-choice answer sheet from captured image. In addition, On-line scoring system is developed and implemented to mark the short-answer type on the reverse side. Therefore, teachers can mark the short-answer type for anytime and anywhere within the available time. There were many advantages to mark of the multiple-choice answer sheet without additional OMR reader. In the future, the grading of short-answer type will be more efficient if it were performed by using an automatic scoring system based on image processing.

• Journal of The Korean Association For Science Education
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• v.30 no.2
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• pp.275-290
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• 2010

In this study, reliabilities of holistic scoring method and analytic scoring method were analyzed in performance assessments of middle school students' science investigation activity. Reliabilities of 2, 3, and 4~7-level rubric ratings for analytic scoring methods were compared to figure out optimized numbers of rubric ratings. Two trained raters rated four activity sheets of 60 students by two rating methods and three kinds of rubric ratings. Internal consistency reliabilities of holistic scoring methods were higher than those of analytic scoring methods, while intrarater reliabilities of analytic scoring were higher than those of holistic scoring methods. Internal consistency reliabilities and intra-rater reliabilities of 3-level rubric rating showed similar patterns of 4~7-level rubric ratings. But students' discriminations, item difficulties and item-response curves showed that the 3-level rubric ratings was reliable. These results suggest that holistic scoring method could be adapted to increase internal consistency reliabilities with improvement in intra-rater reliabilities by rater's conferences. Also, the 3-level rubric rating would be enough for good reliability in case of adapting analytic scoring methods.

• Journal of The Korean Association For Science Education
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• v.25 no.2
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• pp.173-183
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• 2005

In this study, we questioned what assessment types and scoring methods of science performance assessment(SPA) were being used in middle and high school, and how much these SPA scores were reliable(generalizable). To answer these questions, SPA data obtained from the seven schools were classified according to assessment type and scoring method. Based upon this classification, we analyzed the reliability by applying generalizability theory. The result, from the classification of assessment type and scoring method, showed that SPA types of the seven schools were divided into two types: paper-pencil type and task type. Paper-pencil type included answer(content)-restricted essay-type test solely. Task type has two parts: process and outcome assessment. As the results of analyzing scoring methods of the seven schools, there were two cases in the way of scoring methods: one case is scoring all essay-type items and performance tasks by one teacher, the other is scoring assigned performance tasks by two teachers. But the case of scoring assigned essay-type items or the case of cross scoring by two or more teachers were not found. The findings of the reliability analysis are as follows: (1) Effect of essay-type item to SPA score was larger than that of performance task. (2) There was remarkable difference among the seven schools' interaction effect of person and rater in scoring performance tasks. (3) Most of generalizability(reliability) coefficients of SPA for the seven schools were smaller than the acceptable generalizability coefficient(0.80). Therefore, the population of statistical parameters such as number of item, task and rater, should be increased for approaching the acceptable generalizability level.