• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.190-193
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• 2000

In this paper, we investigate the distribution of classification accuracies of multiclass problems in the feature space and analyze performances of the conventional feature extraction algorithms. In order to find the distribution of classification accuracies, we sample the feature space and compute the classification accuracy corresponding to each sampling point. Experimental results showed that there exist much better feature sets that the conventional feature extraction algorithms fail to find. In addition, the distribution of classification accuracies is useful for developing and evaluating the feature extraction algorithm.

• Journal of the Korean Society of Safety
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• v.24 no.6
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• pp.7-12
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• 2009

This study focuses on the classification of fire equipments for certification based on the risk evaluation. In general, known statistics on fire equipment-related accidents needs to be used for risk evaluation. When statistics is not available, however, expected frequency and severity of accident for individual equipment can be taken into account in evaluating the related risks. Based on the level of inherent risks, each equipment is then classified into three categories for certification. For equipments that risk evaluation is not possible, characteristics of those products such as reliability are considered for classification. Once classified, each equipment is assigned an appropriate certification module.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.31-40
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• 2013

In this paper, a novel method is proposed to build an ensemble of classifiers by using a feature selection schema. The feature selection schema identifies the best feature sets that affect the arrhythmia classification. Firstly, a number of feature subsets are extracted by applying the feature selection schema to the original dataset. Then classification models are built by using the each feature subset. Finally, we combine the classification models by adopting a voting approach to form a classification ensemble. The voting approach in our method involves both classification error rate and feature selection rate to calculate the score of the each classifier in the ensemble. In our method, the feature selection rate depends on the extracting order of the feature subsets. In the experiment, we applied our method to arrhythmia dataset and generated three top disjointed feature sets. We then built three classifiers based on the top-three feature subsets and formed the classifier ensemble by using the voting approach. Our method can improve the classification accuracy in high dimensional dataset. The performance of each classifier and the performance of their ensemble were higher than the performance of the classifier that was based on whole feature space of the dataset. The classification performance was improved and a more stable classification model could be constructed with the proposed approach.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.795-801
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• 2013

Recently, support vector machine has been widely used in various application fields due to its superiority of classification performance comparing with decision tree and neural network. Since support vector machine is basically designed for the binary classification problem, output coding method to analyze the classification result of multiclass binary classifier is used for the application of support vector machine into the multiclass problem. However, previous feature selection method for output coding based support vector machine found the features to improve the overall classification accuracy instead of improving each classification accuracy of each classifier. In this paper, we propose the novel feature selection method to find the features for maximizing the classification accuracy of each binary classifier in output coding based support vector machine. Experimental result showed that proposed method significantly improved the classification accuracy comparing with previous feature selection method.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.264-269
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• 2013

Purpose: This study was carried out to develop a classification index and grade levels to rate agricultural heaters for energy efficiency classification. Methods: The classification index was developed mainly by taking simplicity of calculation and easy access to relevant data into consideration. The grade levels were developed on the basis of a 5-grade classification system in which graded heaters are to be normally distributed over the grades. The value of each grade level were determined in terms of the classification index values calculated using the published performance data of agricultural heaters tested at the FACT in Korea over the past 12 years. Results: The thermal efficiency of agricultural heaters based on the enthalpy method was proposed as a reasonable classification index. The grade levels were proposed in equation form for three types of agricultural heaters: fossil fuel heaters, wood pellet heaters and wood pellet boilers. A reasonable energy efficiency classification of agricultural heaters could be performed using the proposed classification index and grade levels. Conclusions: It is expected that energy saving programs will be extended to agricultural machines in the near future. The classification index and grade levels to rate agricultural heaters for energy efficiency classification were developed and proposed for such near future to come.

• Journal of Korean Elementary Science Education
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• v.27 no.1
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• pp.9-22
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• 2008

The purpose of this study was to investigate the type of classification criterion and the characteristic of classification strategy that appear in pre-service elementary teachers' classification activity. The 4 tasks were developed for classification activity; button as a real things that attribute is prominent, shell as a real things that attribute is less prominent, snow flake as a picture cards that attribute is prominent, and galaxy as a picture cards that attribute is less prominent. The 5 college students who major in elementary education were selected. Data were collected by interview with participants, participants' classification recording paper, investigator's observation of participants' action observation, and videotaped that record participants' subject classification process. Result proved in this study is as following. First, pre-service elementary teachers used 4 qualitative classification criterion of feature, random field, image and secondary property, and used 2 dimension classification criterion of space and quantity. They used single quality classification criterion or combining dimension classification criterion in classification activity. Second, pre-service elementary teachers have classification strategy that apply each various classification criterion, and also classification strategy are different according to subject, but discussed that "anchor" and "priming effect" are important for effective classification. Result of this study is expected to contribute classification research and classification teaching program development.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.477-491
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• 1997

A new predictive classification rule for assigning future cases into one of two multivariate normal population (with unknown normal mixture model) is considered. The development involves calculation of posterior probability of each possible normal-mixture model via a default Bayesian test criterion, called intrinsic Bayes factor, and suggests predictive distribution for future cases to be classified that accounts for model uncertainty by weighting the effect of each model by its posterior probabiliy. In this paper, our interest is focused on constructing the classification rule that takes care of uncertainty about the types of covariance matrices (homogeneity/heterogeneity) involved in the model. For the constructed rule, a Monte Carlo simulation study demonstrates routine application and notes benefits over traditional predictive calssification rule by Geisser (1982).

• Korean Journal of Environment and Ecology
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• v.22 no.6
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• pp.666-678
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• 2008

The needs for drawing up of biotope map is rapidly spreaded over each local government recently in Korea, according as enhancing of interest about biotope, which is recognized to practical instrument for concretely being able to considering natural environment and ecosystem on all sorts of development plan. However, there are not yet the standard suggestion on biotope types and classification systems and biotope classification criteria. Therefore, each other methodologies are applied to each of local autonomies. First, under such critical mind the biotope types and classification systems were drafted by a review on biotope types, biotope classification systems, and biotope classification criteria of the preceded case studies until now at the inside and outside of the country. And then the purpose of this study is to derive biotope types and biotope classification systems applicable to the whole Korean region through continual feed back such as field surveys in selected representative areas and consultations. As a result of reviewing the case examples, first, the biotope classification systems were mixed two steps system with three steps system and those were composed mostly of the structure of two steps: large and small. Second, land-use, soil pavement ratio, green cover ratio, and vegetation usually were applied to the biotope classification criteria. This study suggests that the biotope classification system is consisted of four steps system: large(biotope class), medium(biotope group), small(biotope type) and detail(sub-biotope type), and the biotope types are classified into 13 types of large step, 45 types of medium step and 127 types of small step. However, this study suggests that the new biotope types on small step or detail step should be continually supplemented with the foundation of classification system proposed in this study because the biotope type classification should consider regional characteristics.

• Korean Journal of Adult Nursing
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• v.12 no.2
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• pp.256-266
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• 2000

The purpose of this study was to develop and test the validity of the standardized Korean nomenclature of Nursing Outcomes Classification (NOC), developed by Johnson & Maas at the University of Iowa. The four phases of the study were: (1) translation of the NOC into Korean by the research team, (2) four nursing professors and eight nurses with various clinical backgrounds reviewed each nomenclature taking into consideration definitions and nursing activities. The modified Delphi method was used to determine the most appropriate nomenclature for each term; (3) Twenty four academic and clinical experts in nursing were given a questionnaire to rate each Korean nomenclature using a 5 point Likert scale ranging from very inappropriate to very appropriate; (4) the team determined the most appropriate Korean nomenclature for each class of the NOC. The mean validity score of 190 items was 4.54, but several nursing outcome had a score lower than 4.0. They included 'adherence behavior(3.3)', 'ambulation : walking(3.57)', 'transfer performance (3.57)', 'caregiving endurance potential(3.57)'.

• Journal of Soil and Groundwater Environment
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• v.20 no.7
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• pp.1-12
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• 2015

The purpose of this study is to highlight the National Classification System related to cleanup the soil contaminated sites and to provide some guidance to address the priority management rank system before the remediation for Busan metropolitan city. Based on the previous soil investigation data, the quantitative classification of vulnerable areas for soil pollution was performed to successfully manage the contaminated sites in Busan. Ten evaluation factors indicating the high soil pollution possibility were used for the priority management ranking system and 10 point was assigned for each factor which was evenly divided by 10 class intervals. For 16 Gu/Guns in Busan, the score of each evaluation factor was assigned according to the ratio of the area (or the number) between in each Gu (or Gun) and in Busan. Ten scores for each Gu (or Gun) was summed up to prioritize the vulnerable Gu or Guns for soil pollution in Busan. Results will be available to determine the most urgent area to cleanup in each Gu (or Gun) and also to assist the municipal government to design a successful and cost-effective site management strategy in Busan.