• 한국경영과학회지
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• 제27권2호
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• pp.1-13
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• 2002

In this paper, we compares the business failure prediction accuracy among Linear Programming Discriminant Analysis(LPDA) model, Multivariate Discriminant Analysis (MDA) model and logit analysis model. The Data for 417 companies analyzed were gathered from KIS-FAS Published by Korea Information Service in 1999. The result of comparison for four time horizons shows that LPDA Is advantageous in prediction accuracy over the other two models when over all tilt ratio and business failure accuracy are considered simultaneously.

• Communications for Statistical Applications and Methods
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• 제9권2호
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• pp.543-553
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• 2002

Principal component analysis is applied to reduce p-dimensions into q-dimensions ( $q {\leq} p$). Any partition of a collection of data points with p and q variables generated by the application of six hierarchical clustering methods is re-classified by discriminant analysis. From the application of discriminant analysis through each hierarchical clustering method, correct classification ratios are obtained. The results illustrate which method is more reasonable in exploratory data analysis.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.2008-2011
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• 2002

We propose a new numerical algorithm for linear discriminant analysis which makes it possible to update the discriminant functions with very low computational cost.

• 유통과학연구
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• 제17권11호
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• pp.73-79
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• 2019

Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

• 보건행정학회지
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• 제20권3호
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• pp.123-137
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• 2010

The main purpose of this article is for deriving functions related to the prediction of the closure of the hospitals, and finding out how the discriminant functions affect the closure of the hospitals. Empirical data were collected from 3 years financial statements of 41 private hospitals closed down from 2000 till 2006 and 62 private hospitals in business till now. As a result, the functions related to the prediction of the closure of the private hospital are 4 indices: Return on Assets, Operating Margin, Normal Profit Total Assets, Interest expenses to Total borrowings and bonds payable. From these discriminant functions predicting the closure, I found that the profitability indices - Return on Assets, Operating Margin, Normal Profit Total Assets - are the significant affecting factors. The discriminant functions predicting the closure of the group of the hospitals, 3 years before the closure were Normal Profit to Gross Revenues, Total borrowings and bonds payable to total assets, Total Assets Turnover, Total borrowings and bonds payable to Revenues, Interest expenses to Total borrowings and bonds payable and among them Normal Profit to Gross Revenues, Total borrowings and bonds payable to total assets, Total Assets Turnover, Total borrowings and bonds payable to Revenues are the significant affecting factors. However 2 years before the closure, the discriminant functions predicting the closure of the hospital were Interest expenses to Total borrowings and bonds payable and it was the significant affecting factor. And, one year before the closure, the discriminant functions predicting the closure were Total Assets Turnover, Fixed Assets Turnover, Growth Rate of Total Assets, Growth Rate of Revenues, Interest expenses to Revenues, Interest expenses to Total borrowings and bonds payable. Among them, Total Assets Turnover, Growth Rate of Revenues, Interest expenses to Revenues were the significant affecting factors.

• 한국정보통신학회논문지
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• 제22권1호
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• pp.125-130
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• 2018

선형판별분석(LDA) 기법은 특징벡터의 차원을 줄이거나 클래스 식별에 이용되는 통계적 분석 방법이다. 그러나 선형 분리가 불가능한 데이터 집합의 경우에는 비선형 함수를 이용하여 특징벡터를 고차원의 공간으로 사상(mapping) 시켜줌으로써 선형 분리가 가능하도록 만들 수 있는데, 이러한 기법을 일반화된 판별분석(GDA) 또는 커널판별분석(KDA) 기법이라고 한다. 본 연구에서는 인터넷에 공개되어 있는 능동소나 표적신호에 LDA 및 GDA 기법을 이용하여 표적식별 실험을 수행하고, 그 결과를 비교/분석하였다. 실험 결과 104개의 테스트 데이터에 대해 LDA 기법으로는 73.08% 인식률을 얻었으나 GDA 기법으로는 95.19%로 기존의 MLP 또는 커널 기반 SVM에 비해 나은 성능을 보였다.

• 대한수학회보
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• 제57권2호
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• pp.481-488
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• 2020

In this paper we give an exact formula for the Fourier coefficients of the Jacobi-Eisenstein series of square free discriminant lattice index. For a special case the discriminant of lattice is prime we show that the Jacobi-Eisenstein series corresponds to a well known Eisenstein series of modular forms.

• Communications for Statistical Applications and Methods
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• 제4권1호
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• pp.49-63
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• 1997

We consider the problem of classifying a p x 1 observation into one of two multivariate normal populations when the training smaples contain a block of missing observation. A new classification procedure is proposed which is a linear combination of two discriminant functions, one based on the complete samples and the other on the incomplete samples. The new discriminant function is easy to use.

• 대한전자공학회논문지TE
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• 제37권3호
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• pp.16-20
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• 2000

대부분의 음성인식 시스템이 확률 모델을 기반으로 한 HMM 방법을 가장 많이 사용하고 있다. 한국어 고립 전화 숫자음 인식인 경우에 만약 충분한 학습 데이터가 주어지면 HMM 방법을 사용해도 높은 인식률을 얻는다 그러나 한국어 연속 전화 숫자음 인식인 경우에 비슷하게 발음되는 전화 숫자음들에 대해서는 HMM방법이 한계를 가지고 있다. 본 논문에서는 한국어 연속 전화 숫자음 인식에서 HMM 방법의 한계를 극복하기 위해 discriminant 학습 방법을 제시한다. 실험결과는 우리가 제시한 discriminant 학습 방법이 비슷하게 발음되는 전화 숫자음들에 대해서 높은 인식률을 갖는 것을 보여준다.

• 한국멀티미디어학회논문지
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• 제18권7호
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• pp.834-842
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• 2015

We propose a method to construct composite feature vector based on discriminant analysis for face recognition. For this, we first extract the holistic- and local-features from whole face images and local images, which consist of the discriminant pixels, by using a discriminant feature extraction method. In order to utilize both advantages of holistic- and local-features, we evaluate the amount of the discriminative information in each feature and then construct a composite feature vector with only the features that contain a large amount of discriminative information. The experimental results for the FERET, CMU-PIE and Yale B databases show that the proposed composite feature vector has improvement of face recognition performance.