Application of principal component analysis
An Application of Principal Component Analysis to Stock Portfolio Management
... the application of principal component analysis to the Australian stock market using ASX200 index and its constituents from April 2000 to February ...ten principal components were ...
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Application of principal component analysis to multispectral multimodal optical image analysis for malaria diagnostics
... and application of a novel method which uses principal component analysis (PCA) in the processing of spectral images obtained from a simple multispectral-multimodal imaging microscope to ...
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Application of Principal Component Analysis in Reservoir Evaluation
... 2 (The Fourth Oil Production Plant of Daqing Oilfield, Heilongjiang Daqing 163000 ， China) Abstract: - Reservoir heterogeneity is an important basis of exploration and development strategy, so a comprehensive reservoir ...
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Application of Principal Component Analysis Based on In Vitro Antioxidant Capacity
... Interrelationships between different parameters (phenolics, flavonoids, and antioxidant activity) in different fruits and vegetables were investigated by principal component analysis (PCA) and ...
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An application of principal component analysis to the clavicle and clavicle fixation devices
... shape analysis, PCA was applied to study the factors that account for anatomical ...first principal component representing size accounted for ...three principal components accounted for almost ...
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PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm
... the application of PCA to the DCA makes it possible to automatically cat- egorise input data into user-defined signal cate- gories, while still generating useful and accurate classification ...
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Component retention in principal component analysis with application to cDNA microarray data
... this analysis in the paper where we provide an explicit ...data analysis as they provide a reference point with respect to which other methods can be ...
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A Review of Constrained Principal Component Analysis (CPCA) with Application on Bootstrap
... regression analysis, where it was considered an important statistical development of the last fifty years, following general linear model (GLM), principal component analysis (PCA) and ...
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Application of SWOT and Principal Component Analysis in a Textile Company - A Case Study
... SWOT analysis for a leading textile company in south India, aimed at helping the company management to formulate their long range and short range ...SWOT analysis variables, so as to plan their strategy in ...
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A novel incremental principal component analysis and its application for face recognition
... A T A = a low-rank matrix + a multiple of the identity matrix. If a matrix has the low-rank-plus-shift structure, the SVD updating algorithm will obtain the same best low-rank approx- imation as in the batch mode. This ...
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Class-Conditional Probabilistic Principal Component Analysis: application to gender recognition
... Keywords: Gender classification, face analysis, class conditional PPCA. Resumen. Este trabajo presenta una solución al problema del reconocimiento del género de un rostro humano a partir de una imagen. Adoptamos ...
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2 Robust Principal Component Analysis
... to principal component analysis and factor analysis are ...an application we use a large geochemical data set which was analyzed in detail by univariate (geo-)statistical ...
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Sparse generalised principal component analysis
... generalised principal component analysis algorithm (a well-known feature extraction method) to achieve sparse dimension reduction for non-Gaussian ...the application of this method to ...
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Bilinear probabilistic principal component analysis
... The AECM algorithm is a flexible and powerful general- ization of the standard EM [31]. It is well-known that EM performs an E-step to obtain the so-called Q function followed by a M-step to maximize Q with respect to ...
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Adaptive robust principal component analysis
... empirical value used in the existing algorithm. Doing so, on the one hand, will defi- nitely improve the graph quality and eventually lead to better algorithm performance. On the other hand, learning weights, instead of ...
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Principal Component Analysis of Thermographic Data
... the principal components. The application of this approach will demonstrate how these models are used to quickly reduce and quantify defects in large volumes of thermographic ...the application of ...
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A survey of functional principal component analysis
... its application has been limited when the number of variables is less than the sample size of multivariate data; and the multivariate data are equally spaced on a dense ...
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Morphological Principal Component Analysis for Hyperspectral Image Analysis
... an analysis of their corresponding covariance matrix ...The application of MPCA to hyperspectral dimensionality image reduction is considered in Section ...
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Using Principal Component Analysis in Loan Granting
... Introduction In banking domain to know what are the best decisions to make is a permanent concern for managers. An active banking area with higher risk is represented by credit department. Here, credits officers analyze ...
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II. THE CLASSICAL PRINCIPAL COMPONENT ANALYSIS (PCA)
... The following application is one of the examples of PCA which is classical to the process of clustering flowers. There are three categories of flowers; red color for Red Hisbiscus, Purple color for Linum ...
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