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Bayesian Quadratic Discriminant Analysis
- Journal of Machine Learning Research
, 2007
"... Quadratic discriminant analysis is a common tool for classification, but estimation of the Gaussian parameters can be ill-posed. This paper contains theoretical and algorithmic contributions to Bayesian estimation for quadratic discriminant analysis. A distribution-based Bayesian classifier is deriv ..."
Abstract
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Cited by 20 (7 self)
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Quadratic discriminant analysis is a common tool for classification, but estimation of the Gaussian parameters can be ill-posed. This paper contains theoretical and algorithmic contributions to Bayesian estimation for quadratic discriminant analysis. A distribution-based Bayesian classifier
Quadratic Discriminant Analysis Revisited
, 2015
"... This Dissertation is brought to you by CUNY Academic Works. It has been accepted for inclusion in All Dissertations, Theses, and Capstone Projects ..."
Abstract
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This Dissertation is brought to you by CUNY Academic Works. It has been accepted for inclusion in All Dissertations, Theses, and Capstone Projects
Graphical tools for quadratic discriminant analysis
- Technometrics
, 2007
"... Sufficient dimension reduction methods provide effective ways to visualize discriminant anal-ysis problems. For example, Cook and Yin (2001) showed that the dimension reduction method of sliced average variance estimation (save) identifies variates that are equivalent to a quadratic discriminant ana ..."
Abstract
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Cited by 4 (1 self)
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Sufficient dimension reduction methods provide effective ways to visualize discriminant anal-ysis problems. For example, Cook and Yin (2001) showed that the dimension reduction method of sliced average variance estimation (save) identifies variates that are equivalent to a quadratic discriminant
Fourier transform Quadratic discriminant analysis
"... Chilean wine varietal classification using quadratic Fisher ..."
Sparse Quadratic Discriminant Analysis and Community Bayes
, 2014
"... We develop a class of rules spanning the range between quadratic dis-criminant analysis and naive Bayes, through a path of sparse graphical models. A group lasso penalty is used to introduce shrinkage and encour-age a similar pattern of sparsity across precision matrices. It gives sparse estimates o ..."
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We develop a class of rules spanning the range between quadratic dis-criminant analysis and naive Bayes, through a path of sparse graphical models. A group lasso penalty is used to introduce shrinkage and encour-age a similar pattern of sparsity across precision matrices. It gives sparse estimates
Splice site prediction with quadratic discriminant analysis using diversity measure
- Nucleic Acids Research
"... Based on the conservation of nucleotides at splic-ing sites and the features of base composition and base correlation around these sites we use the method of increment of diversity combined with quadratic discriminant analysis (IDQD) to study the dependence structure of splicing sites and predict th ..."
Abstract
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Cited by 10 (2 self)
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Based on the conservation of nucleotides at splic-ing sites and the features of base composition and base correlation around these sites we use the method of increment of diversity combined with quadratic discriminant analysis (IDQD) to study the dependence structure of splicing sites and predict
Quadratic Discriminant Analysis of Spatially Correlated Data’, Nonlinear Analysis: Modelling and Control
- Issues,2
"... The problem of classification of the realisation of the stationary univariate Gaussian random field into one of two populations with different means and different factorised covariance matrices is considered. In such a case optimal classification rule in the sense of minimum probability of misclassi ..."
Abstract
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Cited by 1 (0 self)
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of misclassification is associated with non-linear (quadratic) discriminant function. Unknown means and the covariance matrices of the feature vector components are estimated from spatially correlated training samples using the maximum likelihood approach and assuming spatial correlations to be known. Explicit formula
Regularized discriminant analysis
- J. Amer. Statist. Assoc
, 1989
"... Linear and quadratic discriminant analysis are considered in the small sample high-dimensional setting. Alternatives to the usual maximum likelihood (plug-in) estimates for the covariance matrices are proposed. These alternatives are characterized by two parameters, the values of which are customize ..."
Abstract
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Cited by 468 (2 self)
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Linear and quadratic discriminant analysis are considered in the small sample high-dimensional setting. Alternatives to the usual maximum likelihood (plug-in) estimates for the covariance matrices are proposed. These alternatives are characterized by two parameters, the values of which
Kernel Quadratic Discriminant Analysis for Positive Definite and Indefinite Kernels
"... Abstract — Kernel methods are well established and successful algorithms for pattern analysis thanks to their mathematical elegance and efficient solutions they provide. Numerous nonlinear extensions of pattern recognition techniques have been proposed based on the so-called kernel trick. The object ..."
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. The objective of this paper is twofold. First, we derive an additional kernel tool, namely kernel quadratic discriminant (KQD). We discuss different formulations of KQD based on the regularized kernel Mahalanobis distance in both full and classrelated subspaces. Secondly, we propose suitable extensions
CLASSIFYING LINEAR SYSTEM OUTPUTS BY ROBUST LOCAL BAYESIAN QUADRATIC DISCRIMINANT ANALYSIS ON LINEAR ESTIMATORS
"... ABSTRACT We consider the problem of assigning a class label to the noisy output of a linear system, where clean feature examples are available for training. We design a robust classifier that operates on a linear estimate, with uncertainty modeled by a Gaussian distribution with parameters derived ..."
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from the bias and covariance of a linear estimator. Class-conditional distributions are modeled locally as Gaussians. Since estimation of Gaussian parameters from few training samples can be illposed, we extend recent work in Bayesian quadratic discriminant analysis to derive a robust local generative
Results 1 - 10
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19,628
