# Principal Component Analysis

### PRINCIPAL COMPONENT ANALYSIS

**principal**

**component**

**analysis**. ...

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### Principal Component Analysis

**Principal**

**Component**...

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### Interactive Principal Component Analysis

**principal**

**component**

**analysis**with any statistical software is a black-box experience: you give the data, and then get the result, and then you try to understand what was ...

6

### Comparative Study of Principal Component Analysis and Independent Component Analysis

**analysis**of two most popular subspace projection techniques for face ...compares

**Principal**

**Component**

**Analysis**(PCA) and Independent

**Component**

**Analysis**(ICA), as ...

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### A survey of functional principal component analysis

**analysis**extends existing methodologies and theories from the fields of functional

**analysis**, generalized linear models, multivariate data

**analysis**, nonparametric statistics and many ...data ...

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### Sparse generalised principal component analysis

**principal**

**component**

**analysis**algorithm (a well-known feature extraction method) to achieve sparse dimension reduction for non-Gaussian ...the

**analysis**of text ...

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### Conditions for Robust Principal Component Analysis

**Principal**

**Component**

**Analysis**(PCA) is the problem of finding a low- rank approximation to a ...problem,

**Principal**

**Component**Pursuit (PCP), solves the robust PCA ...

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### A SURVEY: PRINCIPAL COMPONENT ANALYSIS (PCA)

**Principal**

**component**

**analysis**(PCA) is one of the most widely used multivariate techniques in ...called

**principal**components. The number of

**principal**components is less than or ...

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### Principal Component Analysis of Thermographic Data

**Principal**

**Component**

**Analysis**(PCA) has been shown effective for reducing ...

5

### Robust sparse principal component analysis.

**principal**

**component**

**analysis**is proposed that is sparse and robust at the same ...delivers

**principal**components that have loadings on a small number of variables, making them easier to ...

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### Bilinear probabilistic principal component analysis

**Principal**

**component**

**analysis**(PCA) [7] is one of the most popular techniques for dimension reduction. While the standard PCA is nonprobabilistic, Moghaddam and Pentland [8] extended it to a ...

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### 2 Robust Principal Component Analysis

**principal**

**component**

**analysis**and factor

**analysis**are presented. The different methods are compared, and properties are discussed. As an application we use a ...

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### Structured Functional Principal Component Analysis

**principal**

**component**

**analysis**(SFPCA) as a method to decompose the variability via PCA for any functional model with a particular linear ...

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### Morphological Principal Component Analysis for Hyperspectral Image Analysis

**principal**...

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### Using Principal Component Analysis in Loan Granting

**Principal**

**Component**

**Analysis**(PCA) in the banking domain, more exactly in the consumer lending ...The

**principal**

**component**

**analysis**can help in this case to extract those ...

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### II. THE CLASSICAL PRINCIPAL COMPONENT ANALYSIS (PCA)

**Principal**

**Component**

**analysis**, Robust, Vector ...good

**analysis**it is necessary to eliminate the redundant information by creating a new set of variables that extract the essential ...

5

### MFPCA: Multiscale Functional Principal Component Analysis

**principal**

**component**

**analysis**(FPCA) is a key tool for performing dimension reduction on functional data that features infinite dimensionality and emerges in many machine learning ...

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### Towards theory of generic Principal Component Analysis

**Principal**

**Component**

**Analysis**(PCA) which is based on an extension and rigorous justification of the standard PCA. The ...

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### Principal Component Analysis: A Generalized Gini Approach

**principal**

**component**

**analysis**based on the generalized Gini cor- relation index is proposed (Gini PCA). The Gini PCA generalizes the standard PCA based on the ...

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### Multilevel approximate robust principal component analysis

**principal**

**component**

**analysis**(RPCA) is cur- rently the method of choice for recovering a low-rank ma- trix from sparse corruptions that are of unknown value and support by decomposing the ...

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