principal component analysis oor Viëtnamees

principal component analysis

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conversion of a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components
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Nutritional epidemiologists use multivariate statistics, such as principal components analysis and factor analysis, to measure how patterns of dietary behavior influence the risk of developing cancer.
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Popular recognition algorithms include principal component analysis using eigenfaces, linear discriminant analysis, elastic bunch graph matching using the Fisherface algorithm, the hidden Markov model, the multilinear subspace learning using tensor representation, and the neuronal motivated dynamic link matching.
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In 1951, chemical and X-ray analysis confirmed the principal constituents of taaffeite as beryllium, magnesium and aluminium, making taaffeite the first mineral to contain both beryllium and magnesium as essential components.
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