• Title/Summary/Keyword: canonical correlation analysis

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A Canonical Correlation Analysis of Customer Satisfaction for Family Restaurant Dining in Sunchon City (순천시 패밀리레스토랑 이용고객들의 외식만족에 대한 정준상관분석)

  • Kang, Jong-Heon
    • Journal of the Korean Society of Food Culture
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    • v.17 no.2
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    • pp.120-130
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    • 2002
  • The purpose of this study is to investigate whether a group of predictor variables which constitute four determinants of dining satisfaction do exert a significant influence on messures of dining satisfaction in family restaurant. Canonical correlation analysis is used to achieve the purpose of this study. This technique enables the researcher to test for the effects of a set of predictor variables upon a multidimensional measure of dining satisfaction in family restaurant. Results suggest that multiple determinants are important in determining dining satisfaction in family restaurant. No one determinant can fully explain its complexities. The four determinants also appear to vary in terms of importance. Individual variables within four determinants also appear to vary in terms of importance. Finally, the results of the study provide some insight into the types of marketing strategies that can be successfully used by operators who manage family restaurants.

Canonical Correlation Biplot

  • Park, Mi-Ra;Huh, Myung-Hoe
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.11-19
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    • 1996
  • Canonical correlation analysis is a multivariate technique for identifying and quantifying the statistical relationship between two sets of variables. Like most multivariate techniques, the main objective of canonical correlation analysis is to reduce the dimensionality of the dataset. It would be particularly useful if high dimensional data can be represented in a low dimensional space. In this study, we will construct statistical graphs for paired sets of multivariate data. Specifically, plots of the observations as well as the variables are proposed. We discuss the geometric interpretation and goodness-of-fit of the proposed plots. We also provide a numerical example.

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Influence Analysis on a Test Statistic in Canonical Correlation Analysis

  • Jung, Kang-Mo
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.347-355
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    • 2001
  • We propose a method for detecting influential observations that have a large influence on the likelihood ratio test statistic for the two sets of variables are uncorrelated with one another. For this purpose we derive a local influence measure for the likelihood ratio test statistic under certain perturbation scheme. An illustrative example is given to show the effectiveness of the proposed method on the identification of influential observations.

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Minimax Eccentricity Estimation for Multiple Set Factor Analysis

  • Hyuncheol Kang;Kim, Keeyoung
    • Journal of the Korean Statistical Society
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    • v.31 no.2
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    • pp.163-175
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    • 2002
  • An extended version of the minimax eccentricity factor estimation for multiple set case is proposed. In addition, two more simple methods for multiple set factor analysis exploiting the concept of generalized canonical correlation analysis is suggested. Finally, a certain connection between the generalized canonical correlation analysis and the multiple set factor analysis is derived which helps us clarify the relationship.

Quantification Plots for Several Sets of Variables

  • Park, Mira;Huh, Myung-Hoe
    • Journal of the Korean Statistical Society
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    • v.25 no.4
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    • pp.589-601
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    • 1996
  • Geometric approach to extend the classical two-set theory of canonical correlation analysis to three or more sets is considered. It provides statistical graphs to represent the data in a low dimensional space. Procedures are developed for computing the canonical variables and the corresponding properties are investigated. The solution is equivalent to that of the usual problem in the case of two sets. Goodness-of-fit of the proposed plots is studied and a numerical example is included.

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A time delay estimation method using canonical correlation analysis and log-sum regularization (로그-합 규준화와 정준형 상관 분석을 이용한 시간 지연 추정에 관한 연구)

  • Lim, Jun-Seok;Pyeon, Yong-Gook;Lee, Seokjin;Cheong, MyoungJun
    • The Journal of the Acoustical Society of Korea
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    • v.36 no.4
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    • pp.279-284
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    • 2017
  • The localization of sources has a numerous number of applications. To estimate the position of sources, the relative time delay between two or more received signals for the direct signal must be determined. Although the GCC (Generalized Cross-Correlation) method is the most popular technique, an approach based on CCA (Canonical Correlation Analysis) was also proposed for the TDE (Time Delay Estimation). In this paper, we propose a new adaptive algorithm based on CCA in order to utilized the sparsity in the eigenvector of CCA based time delay estimator. The proposed algorithm uses the eigenvector corresponding to the maximum eigenvalue with log-sum regularization in order to utilize the sparsity in the eigenvector. We have performed simulations for several SNR(signal to noise ratio)s, showing that the new CCA based algorithm can estimate the time delays more accurately than the conventional CCA and GCC based TDE algorithms.

A Study on the Relationship between Physique, Physical Fitness and Basic Skill Factors of Tennis Players in the Korea Tennis Association Using the Generalized Canonical Correlation Biplot and Procrustes Analysis (일반화 정준상관 행렬도와 프로크러스티즈 분석을 응용한 대한테니스협회 등록 선수의 체격요인, 체력요인 및 기초기술요인에 대한 분석연구)

  • Choi, Tae-Hoon;Choi, Yong-Seok
    • Communications for Statistical Applications and Methods
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    • v.17 no.6
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    • pp.917-925
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    • 2010
  • The canonical correlation biplot is a 2-dimensional plot for graphically investigating the relationship between two sets of variables and the relationship between observations and variables in the canonical correlation analysis. Recently, Choi and Choi (2008) suggested a method for investigating the relationship between skill and competition score factors of KLPGA players using this biplot. Choi et al. (2010) used this biplot to analyze the player characteristic factors and competitive factors of tennis Grand Slam competition. Moreover, Huh (1999) provided a generalized canonical correlation analysis and biplot for more than three sets of variables. A Procrustes analysis is a useful tool for comparing shapes between configurations. This study will provide a method to investigate the relationship between physique, physical fitness and basic skill factors of tennis players in the Korea Tennis Association using a generalized canonical correlation biplot and Procrustes analysis.

Development of Classification Method for the Remote Sensing Digital Image Using Canonical Correlation Analysis (정준상관분석을 이용한 원격탐사 수치화상 분류기법의 개발 : 무감독분류기법과 정준상관분석의 통합 알고리즘)

  • Kim, Yong-Il;Kim, Dong-Hyun;Park, Min-Ho
    • Journal of Korean Society for Geospatial Information Science
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    • v.4 no.2 s.8
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    • pp.181-193
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    • 1996
  • A new technique for land cover classification which applies digital image pre-classified by unsupervised classification technique, clustering, to Canonical Correlation Analysis(CCA) was proposed in this paper. Compared with maximum likelihood classification, the proposed technique had a good flexibility in selecting training areas. This implies that any selected position of training areas has few effects on classification results. Land cover of each cluster designated by CCA after clustering is able to be used as prior information for maximum likelihood classification. In case that the same training areas are used, accuracy of classification using Canonical Correlation Analysis after cluster analysis is better than that of maximum likelihood classification. Therefore, a new technique proposed in this study will be able to be put to practical use. Moreover this will play an important role in the construction of GIS database

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Local Feature Learning using Deep Canonical Correlation Analysis for Heterogeneous Face Recognition (이질적 얼굴인식을 위한 심층 정준상관분석을 이용한 지역적 얼굴 특징 학습 방법)

  • Choi, Yeoreum;Kim, Hyung-Il;Ro, Yong Man
    • Journal of Korea Multimedia Society
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    • v.19 no.5
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    • pp.848-855
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    • 2016
  • Face recognition has received a great deal of attention for the wide range of applications in real-world scenario. In this scenario, mismatches (so called heterogeneity) in terms of resolution and illumination between gallery and test face images are inevitable due to the different capturing conditions. In order to deal with the mismatch problem, we propose a local feature learning method using deep canonical correlation analysis (DCCA) for heterogeneous face recognition. By the DCCA, we can effectively reduce the mismatch between the gallery and the test face images. Furthermore, the proposed local feature learned by the DCCA is able to enhance the discriminative power by using facial local structure information. Through the experiments on two different scenarios (i.e., matching near-infrared to visible face images and matching low-resolution to high-resolution face images), we could validate the effectiveness of the proposed method in terms of recognition accuracy using publicly available databases.