Principal component analysis

Known as: Principle components analysis, Principle component analysis, Probabilistic principal component analysis 
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly… (More)
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1936-2019
19401960198020002020
Principal component analysis
Numerical analysis
Cluster analysis
Feature extraction
K-means clustering
Mutual information

Papers overview

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Highly Cited
2009
Highly Cited
2009
Principal component analysis
Principal component analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by… (More)
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Highly Cited
2004
Highly Cited
2004
Sparse Principal Component Analysis
Principal component analysis (PCA) is widely used in data processing and dimensionality reduction. However, PCA suffers from the… (More)
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Highly Cited
2004
Highly Cited
2004
K-means clustering via principal component analysis
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means… (More)
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Highly Cited
2004
Highly Cited
2004
Nonlinear Principal Component Analysis Using Autoassociative Neural Networks
Nonlinear principal component analysis is a novel technique for multivariate data analysis, similar to the well-known method of… (More)
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Highly Cited
2003
Highly Cited
2003
Generalized principal component analysis (GPCA)
This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and… (More)
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Highly Cited
2001
Highly Cited
2001
Principal component analysis for clustering gene expression data
MOTIVATION There is a great need to develop analytical methodology to analyze and to exploit the information contained in gene… (More)
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Highly Cited
1998
Highly Cited
1998
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
A new method for performing a nonlinear form of principal component analysis is proposed. By the use of integral operator kernel… (More)
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Highly Cited
1997
Highly Cited
1997
Probabilistic Principal Component Analysis
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org… (More)
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Highly Cited
1997
Highly Cited
1997
Dimension Reduction by Local Principal Component Analysis
Reducing or eliminating statistical redundancy between the components of high-dimensional vector data enables a lower-dimensional… (More)
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Highly Cited
1994
Highly Cited
1994
Independent component analysis, A new concept?
The independent component analysis (ICA) of a random vector consists of searching for a linear transformation that minimizes the… (More)
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