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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Topic mentions per year

1942-2019
01000200019422018

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Highly Cited
2009
Highly Cited
2009
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
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
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 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
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
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
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
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
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
The independent component analysis (ICA) of a random vector consists of searching for a linear transformation that minimizes the… (More)
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