• Title, Summary, Keyword: 판별분석

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그래픽스를 이용한 판별분석법

  • 김성주
    • Communications for Statistical Applications and Methods
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    • v.2 no.2
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    • pp.414-422
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    • 1995
  • 본 논문에서는 그래픽스에 의한 판별분석을 다루고 있다. 본 논문에서 제안하는 새로운 그래프는 표본이차판별함수에 기초하고 있으며 기존의 MV 그래프와 실제자료에 대하여 비교하고 있다. 판별분석에서 공분한행렬이 같지 않은 경우의 3차원 그래프는 처음 시도된 것으로 이를 위하여 차원축소문제를 논의하고 있다.

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Local Linear Logistic Classification of Microarray Data Using Orthogonal Components (직교요인을 이용한 국소선형 로지스틱 마이크로어레이 자료의 판별분석)

  • Baek, Jang-Sun;Son, Young-Sook
    • The Korean Journal of Applied Statistics
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    • v.19 no.3
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    • pp.587-598
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    • 2006
  • The number of variables exceeds the number of samples in microarray data. We propose a nonparametric local linear logistic classification procedure using orthogonal components for classifying high-dimensional microarray data. The proposed method is based on the local likelihood and can be applied to multi-class classification. We applied the local linear logistic classification method using PCA, PLS, and factor analysis components as new features to Leukemia data and colon data, and compare the performance of the proposed method with the conventional statistical classification procedures. The proposed method outperforms the conventional ones for each component, and PLS has shown best performance when it is embedded in the proposed method among the three orthogonal components.

A Comparative Study of Classification Methods Using Data with Label Noise (레이블 노이즈가 존재하는 자료의 판별분석 방법 비교연구)

  • Kwon, So Young;Kim, Kyoung Hee
    • Journal of the Korean Data Analysis Society
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    • v.20 no.6
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    • pp.2853-2864
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    • 2018
  • Discriminant analysis predicts a class label of a new observation with an unknown label, using information from the existing labeled data. Hence, observed labels play a critical role in the analysis and we usually assume that these labels are correct. If the observed label contains an error, the data has label noise. Label noise can frequently occur in real data, which would affect classification performance. In order to resolve this, a comparative study was carried out using simulated data with label noise. In particular, we considered 4 different classification techniques such as LDA (linear discriminant analysis classifiers), QDA (quadratic discriminant analysis classifiers), KNN (k-nearest neighbour), and SVM (support vector machine). Then we evaluated each method via average accuracy using generated data from various scenarios. The effect of label noise was investigated through its occurrence rate and type (noise location). We confirmed that the label noise is a significant factor influencing the classification performance.

IPAA의 효과를 고찰하기 위한 분류분석방법들의 비교연구

  • Lee, Seung-Yeon;Lee, Eun-Ju;Choe, Ho-Sik
    • Proceedings of the Korean Statistical Society Conference
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    • pp.291-298
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    • 2005
  • 지속성 외래 복막투석은 말기 신부전 환자들에게 널리 시행하는 신 대체 요법으로, 복막투석 환자에게서 주된 합병증으로 일어나는 단백질-열량 영양실조를 치료하기 위하여 아미노산을 복강 내로 주입하는 치료방법이다. 이현석 등(2004)의 연구에서는 아미노산 복막 투석액(IPAA)이 영양실조 환자들에게 실제로 영양상태에 미치는 영향을 평가하기 위하여 지속성 외래 복막투석 환자 43명을 12개월 동안 3개월 주기로 관측하여 얻어낸 반복측정자료를 바탕으로 IPAA의 효과 여부에 따라 반응군과 비반응군을 분류하였다. 본 논문에서는 이러한 두 그룹을 효과적으로 분류할 수 있는 분류기준변수들을 찾아내고 이 분류기준변수의 값을 바탕으로 새로운 환자에게 IPAA의 투여 여부를 진단할 수 있는 여러 분류방법들을 고찰하여 비교 연구하였다. 모수적인 방법으로 선형판별분석, 이차판별분석 및 로지스틱 판별분석을 소개하고 비모수적인 방법으로 support vector machine(SVM)을 소개하여 분류분석의 결과를 비교하여 두 그룹을 최소한의 오류로 분류하는 방법을 제안하였다.

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Steal Success Model for 2007 Korean Professional Baseball Games (2007년 한국프로야구에서 도루성공모형)

  • Hong, Chong-Sun;Choi, Jeong-Min
    • The Korean Journal of Applied Statistics
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    • v.21 no.3
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    • pp.455-468
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    • 2008
  • Based on the huge baseball game records, the steal plays an important role to affect the result of games. For the research about success or failure of the steal in baseball games, logistic regression models are developed based on 2007 Korean professional baseball games. The analyses of logistic regression models are compared of those of the discriminant models. It is found that the performance of the logistic regression analysis is more efficient than that of the discriminant analysis. Also, we consider an alternative logistic regression model based on categorical data which are transformed from uneasy obtainable continuous data.

Derivation and Application of In uence Function in Discriminant Analysis for Three Groups (세 집단 판별분석 상황에서의 영향함수 유도 및 그 응용)

  • Lee, Hae-Jung;Kim, Hong-Gie
    • The Korean Journal of Applied Statistics
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    • v.24 no.5
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    • pp.941-949
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    • 2011
  • The influence function is used to develop criteria to detect outliers in discriminant analysis. We derive the influence function of observations that estimate the the misclassification probability in discriminant analysis for three groups. The proposed measures are applied to the facial image data to define outliers and redo the discriminant analysis excluding the outliers. The study proves that the derived influence function is more efficient than using the discriminant probability approach.

Evaluation of Corporate Distress Prediction Power using the Discriminant Analysis: The Case of First-Class Hotels in Seoul (판별분석에 의한 기업부실예측력 평가: 서울지역 특1급 호텔 사례 분석)

  • Kim, Si-Joong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.10
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    • pp.520-526
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    • 2016
  • This study aims to develop a distress prediction model, in order to evaluate the distress prediction power for first-class hotels and to calculate the average financial ratio in the Seoul area by using the financial ratios of hotels in 2015. The sample data was collected from 19 first-class hotels in Seoul and the financial ratios extracted from 14 of these 19 hotels. The results show firstly that the seven financial ratios, viz. the current ratio, total borrowings and bonds payable to total assets, interest coverage ratio to operating income, operating income to sales, net income to stockholders' equity, ratio of cash flows from operating activities to sales and total assets turnover, enable the top-level corporations to be discriminated from the failed corporations and, secondly, by using these seven financial ratios, a discriminant function which classifies the corporations into top-level and failed ones is estimated by linear multiple discriminant analysis. The accuracy of prediction of this discriminant capability turned out to be 87.9%. The accuracy of the estimates obtained by discriminant analysis indicates that the distress prediction model's distress prediction power is 78.95%. According to the analysis results, hotel management groups which administrate low level corporations need to focus on the classification of these seven financial ratios. Furthermore, hotel corporations have very different financial structures and failure prediction indicators from other industries. In accordance with this finding, for the development of credit evaluation systems for such hotel corporations, there is a need for systems to be developed that reflect hotel corporations' financial features.

Identification of geographical origin of sesame seeds by near infrared spectroscopy (근적외 분석법에 의한 참깨의 원산지 판별)

  • Kwon, Young-Kil;Cho, Rae-Kwang
    • Applied Biological Chemistry
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    • v.41 no.3
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    • pp.240-246
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    • 1998
  • Geographical origin of the Korean, Chinese and Japanese sesame seeds were identified very high accuracy by NIR spectroscopy. The NIR instrument of filter type showed the same accuracy of the monochromator scanning type to identify the geographical origin of the sesame seeds. In case of adulteration between the Korean and Chinese sesame seeds, the ratio of addition could be determined about 10% error level. The reason of identification of geographical origin by NIR spectroscopy, it was supposed to the difference, of oil cake substance.

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중풍의 증형 진단을 위한 판별모형

  • Sin, Yang-Gyu
    • Journal of the Korean Data and Information Science Society
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    • v.7 no.2
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    • pp.283-287
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    • 1996
  • 본 연구는 중풍에서의 한의학의 풍부한 임상자료들에 대한 객관적이고도 논리적인 자료처리방법 및 변증으로부터 증형을 추론할 수 있는 통계적 방법을 연구하고자 한다. 중풍 전문의에 의해 수집된 65명의 환자들의 임상자료로부터 다변량 자료 분석의 하나인 판별분석을 이용하여 증후로부터 증형을 판단할 수 있는 수리적 판별모형을 구축하였다. 구축된 모형은 중풍 전문가 시스템을 개발하기 위한 기초가 될 것이다.

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Palatability Grading Analysis of Hanwoo Beef using Sensory Properties and Discriminant Analysis (관능특성 및 판별함수를 이용한 한우고기 맛 등급 분석)

  • Cho, Soo-Hyun;Seo, Gu-Reo-Un-Dal-Nim;Kim, Dong-Hun;Kim, Jae-Hee
    • Food Science of Animal Resources
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    • v.29 no.1
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    • pp.132-139
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    • 2009
  • The objective of this study was to investigate the most effective analysis methods for palatability grading of Hanwoo beef by comparing the results of discriminant analysis with sensory data. The sensory data were obtained from sensory testing by 1,300 consumers evaluated tenderness, juiciness, flavor-likeness and overall acceptability of Hanwoo beef samples prepared by boiling, roasting and grilling cooking methods. For the discriminant analysis with one factor, overall acceptability, the linear discriminant functions and the non-parametric discriminant function with the Gaussian kernel were estimated. The linear discriminant functions were simple and easy to understand while the non-parametric discriminant functions were not explicit and had the problem of selection of kernel function and bandwidth. With the three palatability factors such as tenderness, juiciness and flavor-likeness, the canonical discriminant analysis was used and the ability of classification was calculated with the accurate classification rate and the error rate. The canonical discriminant analysis did not need the specific distributional assumptions and only used the principal component and canonical correlation. Also, it contained the function of 3 factors (tenderness, juiciness and flavor-likeness) and accurate classification rate was similar with the other discriminant methods. Therefore, the canonical discriminant analysis was the most proper method to analyze the palatability grading of Hanwoo beef.