• Safety and Health at Work
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• v.5 no.3
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• pp.161-164
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• 2014

Obesity is a significant problem affecting United States (US) firefighters. While body mass index (BMI) is widely used to diagnose obesity, its use for this occupational group has raised concerns about validity. We examined rates and types of misclassification of BMI-based obesity status compared to body fat percentage (BF%) and waist circumference (WC). Male career firefighters (N = 994) from 20 US departments completed all three body composition assessments. Mean BMI, BF%, and WC were $29kg/m^2$, 23%, and 97 cm, respectively. Approximately 33% and 15% of BF%- and WC-defined obese participants were misclassified as non-obese (false negatives) using BMI, while 8% and 9% of non-obese participants defined by BF% and WC standards were identified as obese (false positives) using BMI. When stratified by race/ethnicity, Pacific Islanders showed high rates of false positive misclassification. Precision in obesity classification would be improved by using WC along with BMI to determine firefighters' weight status.

• Journal of Korean Society of Forest Science
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• v.58 no.1
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• pp.48-53
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• 1982

This experiment was carried out to distinguish between picea abies (L.) Karsten and Picea koraiensis Nak by the method of discriminant analysis which is used the metrical continuous characteristic on current inorphological plant taxanomy. The results are summarized as follows 1) The discriminant function and discriminant region from the experiment are Z(x)=Z($x_1,\;x_2$)=$0.000379x_1+0.004354x_2-0.311061$ or Z(x)=Z($x_1,\;x_2$=$0.000379(x_1-60.442800)+0.004354(x_2-66.185100)$, $$R_1=(x{\mid}0.000379x_1+0.004354x_2-0.311061{\geq_-}0)$$, $R_2$=($x{\mid}0.000379x_1+0.004354x_2-0.311061$ <0). 2) The probability of misclassification based on the above discriminant region is P($2{\mid}1$)=$P(1{\mid}2)$=0.444 therefore the probability of simultaneous misclassification of P($2{\mid}1$) and $P(1{\mid}2)$ is about 44.4%. 3) the probability of misclassification by the discriminant function resulted from the experiment if recorded as high but it is thought that there is a considerable meaning to perceive the probability of confidence about the discrimination better than its precision.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2002.11a
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• pp.430-433
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• 2002

본 논문에서는 얼굴인식을 위해 기존의 Fisherfaces와 퍼지개념을 도입한 퍼지 기반 Fisherfaces 방법을 제안한다. 기존의 얼굴인식 방법들은 학습영상에 해당되는 각 특징벡터에 대해 특정한 클래스를 할당하지만, 이와는 달리 제안된 방법은 각 특징벡터에 대해 퍼지 값으로 된 클래스 소속도를 부여하여 조명의 방향, 얼굴표정과 같은 큰 변화에 민감하지 않으면서도 닮은 얼굴 영상으로 인해 생기는 오분류(misclassification)의 문제점을 해결하고자 한다. 따라서, 본 논문에서는 ORL(Olivetti Research Laboratory) 얼굴 데이터 베이스에 대해 적용하여 이전의 연구인 Eigenfaces와 Fisherfaces보다 더 좋은 인식성능을 보이고자 한다.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.757-764
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• 2009

In discriminant analysis, we consider a special pattern which contains a block of missing observations. We assume that the two populations are equally likely and the costs of misclassification are equal. In this situation, we consider the bootstrap confidence intervals of the error rate in the circular models when the covariance matrices are equal and not equal.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.793-802
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• 1997

A sampling plan is presented for situations where sampling inspection is based on the quality characteristic of interest and items in rejected lots are screened based on a correlated variable. A cost model is constructed which involves the costs of misclassification errors, sampling and screening inspections. A method of finding optimal values of sample size, acceptance number and cutoff value on the correlated variable is presented, and numerical studies are given.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.471-478
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• 2003

In this paper, we reconsider the Kolmogorov-Smirnoff distance as a split criterion for binary decision trees and suggest an algorithm to obtain the Kolmogorov-Smirnoff distance more efficiently when the input variable have more than three categories. The Kolmogorov-Smirnoff distance is shown to have the property of exclusive preference. Empirical results, comparing the Kolmogorov-Smirnoff distance to the Gini index, show that the Kolmogorov-Smirnoff distance grows more accurate trees in terms of misclassification rate.

• Journal of Korean Society for Quality Management
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• v.22 no.1
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• pp.142-151
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• 1994

Optimum screening procedures using prior information are presented. An optimal cutoff value on the screening variable X minimizing the expected total cost is obtained for the normal model; it is assumed that a continuous screening variable X given a dichotomous performance variable T is normally distributed and that costs are incurred by screening inspection and misclassification errors. Methods for finding optimal cutoff values based on the prior distributions for unknown parameters are presented.

• Journal of the Korean Data and Information Science Society
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• v.19 no.1
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• pp.25-36
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• 2008

Error Correcting Output Codes (ECOC) can improve generalization performance when applied to multicategory classification problem. In this study we propose a new criterion to select hyperparameters included in ECOC scheme. Instead of margins of a data we propose to use the probability of misclassification error since it makes the criterion simple. Using this we obtain an upper bound of leave-one-out error of OVA(one vs all) method. Our experiments from real and synthetic data indicate that the bound leads to good estimates of parameters.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.675-686
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• 2009

In this paper, it will be assumed that there are two distinct populations which are multivariate normal with equal covariance matrix. We also assume that the two populations are equally likely and the costs of misclassification are equal. The classification rule depends on the situation when the training samples include missing values or not. We consider the bootstrap confidence intervals for classification error rate when a block of observation is missing.

• Journal of Korean Society for Quality Management
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• v.15 no.1
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• pp.68-75
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• 1987

A rectifying inspection plan is considered for the case of destructive testing. Screening inspection for rejected lots is performed by some nondestructive testing which is prone to misclassification errors. Apparent defectives found in the screening process is replaced with apparent good items. The plan provides LTPD protection on each individual lot while the sum of the cost of testing and the cost due to producer's risk at process average quality is minimized. A brief discussion on average outgoing quality is also given.