Results 241 to 250 of about 426,008 (281)
Classifiability-Based Discriminatory Projection Pursuit
IEEE Transactions on Neural Networks, 2011 Fisher's linear discriminant (FLD) is one of the most widely used linear feature extraction method, especially in many visual computation tasks. Based on the analysis on several limitations of the traditional FLD, this paper attempts to propose a new computational paradigm for discriminative linear feature extraction, named "classifiability-based ...
Yu Su 0009 +3 more
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Skewness-based projection pursuit: A computational approach
Computational Statistics and Data Analysis, 2018 Projection pursuit is a multivariate statistical technique aimed at finding interesting low-dimensional data projections by maximizing a measure of interestingness commonly known as projection index. Widespread use of projection pursuit has been hampered
Nicola Loperfido
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Journal of the Royal Statistical Society. Series A (General), 1987
The paper gives an overview of projection pursuit problems. It explains the background, connections with other multivariate data processing methods and relations of the present authors' work with other ones. Types of projection indexes (Friedman-Tuckey, entropy, moment, or cumulant) for one-dimensional and two-dimensional projections as well as ...
Jones, M. C., Sibson, Robin
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The paper gives an overview of projection pursuit problems. It explains the background, connections with other multivariate data processing methods and relations of the present authors' work with other ones. Types of projection indexes (Friedman-Tuckey, entropy, moment, or cumulant) for one-dimensional and two-dimensional projections as well as ...
Jones, M. C., Sibson, Robin
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Tensor eigenvectors for projection pursuit
TEST, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Projection Pursuit Multivariate Transform
Mathematical Geosciences, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Barnett, Ryan M. +2 more
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Implementing projection pursuit learning
IEEE Transactions on Neural Networks, 1996This paper examines the implementation of projection pursuit regression (PPR) in the context of machine learning and neural networks. We propose a parametric PPR with direct training which achieves improved training speed and accuracy when compared with nonparametric PPR.
Ying Zhao 0006, Christopher G. Atkeson
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Kernel exploratory projection pursuit
KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516), 2002Kernel methods are a recent innovation allowing one to perform efficient linear operations in a nonlinear space with the net effect of having nonlinear operations in data space. We derive three different methods of performing exploratory projection pursuit in kernel space and show on a standard data set that each gives interesting but different ...
Donald MacDonald +2 more
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Projection pursuit discriminant analysis [PDF]
Computational Statistics & Data Analysis, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Generalized projection pursuit regression
SIAM Journal on Scientific Computing, 1998Summary: Projection pursuit regression (PPR) can be used to estimate a smooth function of several variables from noisy and scattered data. The estimate is a sum of smoothed one-dimensional projections of the variables. This paper discusses an extension of PPR to exponential family distributions, called generalized projection pursuit regression (GPPR ...
Ole Christian Lingjærde, Knut Liestøl
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Projection pursuit autoregression and projection pursuit moving average
Proceedings of 1994 Workshop on Information Theory and Statistics, 2002Projection pursuit autoregression (MPPAR) and projection pursuit moving average (MPPMA) with multivariate polynomials as ridge functions in both cases are proposed in this paper. The L/sub 2/-convergence of the methods is proved. This paper also proposes two new algorithms for MPPAR and MPPMA.
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