Results 281 to 290 of about 2,261,156 (339)

Scrub typhus-associated movement and gait disorders: A systematic review with principal component analysis and in silico mechanistic modelling. [PDF]

Trop Med Int Health
Mondal R, Deb S, Dhauria M, Sen P, Sarkar V, Sarkar S, Chowdhury D, Lahiri D, Roy J, Benito-León J.   +9 more
europepmc   +1 more source

Morphological and biochemical adaptations of finger millet (Eleusine coracana) to salinity stress: A principal component analysis

N. Monisha, M. Baskar, S. Meena, S Rathika, V. Dhanushkodi, Nagarajan Madasamy, R L Meena   +6 more
openalex   +2 more sources

Subtype identification of clinical and thrombus imaging features in acute ischemic stroke: using clustering analysis and principal component analysis. [PDF]

Sci Rep
Wu W, Cheng Y, Chen L, Fu Q, Jiang J, Zhang L, Wang X.   +6 more
europepmc   +1 more source

Selection index for economically important traits in Boer crossbred goats using principal component analysis. [PDF]

PLoS One
Tesema Z, Deribe B, Tilahun M, Kefale A, Lakew M, Getachew T, Alebachew GW, Gizaw S.   +7 more
europepmc   +1 more source

Geochemical Anomaly Detection and Pattern Recognition: A Combined Study of the Apriori Algorithm, Principal Component Analysis, and Spectral Clustering

Mahsa Hajihosseinlou, Abbas Maghsoudi, Reza Ghezelbash   +2 more
openalex   +1 more source

Dietary amino acids and the odds of metabolic dysfunction-associated fatty liver disease (MAFLD) among overweight and obese children and adolescents: a principal component analysis approach. [PDF]

Nutr Metab (Lond)
Nikparast A, Mirzaei P, Sohouli MH, Tadayoni ZS, Behrad D, Razavi M, Rohani P, Asghari G.   +7 more
europepmc   +1 more source

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Principal Components Analysis

2012
Principal components analysis (PCA) is a standard tool in multivariate data analysis to reduce the number of dimensions, while retaining as much as possible of the data's variation. Instead of investigating thousands of original variables, the first few components containing the majority of the data's variation are explored.
Detlef, Groth, Stefanie, Hartmann, Sebastian, Klie, Joachim, Selbig   +3 more
openaire   +2 more sources

Coupled Principal Component Analysis

IEEE Transactions on Neural Networks, 2004
A framework for a class of coupled principal component learning rules is presented. In coupled rules, eigenvectors and eigenvalues of a covariance matrix are simultaneously estimated in coupled equations. Coupled rules can mitigate the stability-speed problem affecting noncoupled learning rules, since the convergence speed in all eigendirections of the
Möller, Ralf, Könies, Axel
openaire   +3 more sources

Directed Principal Component Analysis

Operations Research, 2014
We consider a problem involving estimation of a high-dimensional covariance matrix that is the sum of a diagonal matrix and a low-rank matrix, and making a decision based on the resulting estimate. Such problems arise, for example, in portfolio management, where a common approach employs principal component analysis (PCA) to estimate factors used in ...
Kao, Yi-Hao, Van Roy, Benjamin
openaire   +2 more sources