principal component analysis
Top PDF principal component analysis:
Potential species distribution modeling and the use of principal component analysis as predictor variables
... Through principal component analysis (PCA) the 2 sets of original variables were transformed into 4 different sets to produce the species distribution models with the modeling application in ...
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Class-Conditional Probabilistic Principal Component Analysis: application to gender recognition
... Probabilistic Principal Component Analysis (CC-PPCA) technique to reduce the dimensionality of the classification attribute vector and enforce the independence assumption of the ...
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Performance analysis and anomaly detection in wind turbines based on neural networks and principal component analysis
... performance analysis and anomaly detection (PAAD) which can detect anomalies and point out the origin of the detected ...applies principal component analysis (PCA) technique to uncover the ...
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Data Reduction and Regression Using Principal Component Analysis in Qualitative Spatial Reasoning and Health Informatics
... of principal component analysis (PCA) is to reduce the dimensionality of a dataset consisting of a large number of interrelated variables, while retaining as much as possible of the variation present ...
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Principal component analysis for automatic tag suggestion / Enrique Estellés Arolas, Fernando González Ladrón de Guevara and Antonio Falcó Montesinos
... In an attempt to solve these problems, some SBS have reached an agreement on the use of a limited vocabulary. A way to use this limited vocabulary is applied in the SBS Delicious: when a user starts introducing a tag, ...
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Robust Principal Component Analysis Based On Trimming Around Affine Subspaces
... Principal Component Analysis (PCA) is a technique for reducing dimen- sionality in multivariate data analysis. For p-dimensional observations, and a given dimension d, with d typically much ...
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Forescat modeling of spatio-temporal raster data using principal component analysis and a neural networks - wavelet decomposition model
... a principal component analysis, then 2) individual forecasts on the most significant components or eigenvectors are calculated using a neural networks - wavelet decomposition ...
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Burst Detection in Water Networks Using Principal Component Analysis
... called Principal Component Analysis (PCA), allows for a sensitive and quick analysis of the inflows into a DMA without hassling mathematical ...
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Facial Expression Recognition using kernel principal component analysis (KPCA)
... kernel principal component analysis using the Carnegie Mellon University database as a testing ...with principal component analysis and discussed where the percentages of sucess ...
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Estimation of the underlying structure of systematic risk with the use of principal component analysis and factor analysis
... of Principal Component Analysis and Factor ...the Principal Component Analysis and the Maximum Likelihood Factor Analysis ...
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Analysis of multiple waveforms by means of functional principal component analysis: normal versus pathological patterns in sit to stand movement
... This paper presents an application of Functional Principal Component Analysis (FPCA) to describe inter-subject variability of multiple waveforms. This technique was applied to the study of ...
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Regionalization and classification of bioclimatic zones in the central-northeastern region of México using principal component analysis (PCA)
... We use a combination of nearly 30 years of monthly means of temperature and precipitation data from 173 meteorological stations to carry out a climate classification of the state of San Luis Potosí, México. PCA ...
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A Data driven Study of RR Lyrae Near IR Light Curves: Principal Component Analysis, Robust Fits, and Metallicity Estimates
... second component can make the bump at the end of the rising branch ( around phase ...third component is important to reproduce the double-peaked light curves displayed by some of the ...
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Fault Detection and Diagnosis in a Heat Exchanger Using Dynamic Principal Component Analysis and Diagnostic Observers-Edición Única
... 5.9 Diagnostic result for emulated faults in the actuators (cases [1 2]) 50 5.10 Diagnostic result for emulated faults in the actuators (cases [3 4]) 51 5.11 Fault detection result[r] ...
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Principal component analysis applied to continuation power flow
... The simulation considers a single bus – load equivalent and controlled variation of the equivalent system impedance behind the load. Variations of data structure are proposed and analyzed in order to interpret results ...
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Wine science in the metabolomics era
... approaches used in wine metabolomics studies are principal component analysis PCA.. is based on dimension reduction and is often used as a preprocessing step prior to the.[r] ...
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Classification of Imaginary motor task from Electroencephalographic Signals: A Comparison of Feature Selection Methods and Classification Algorithms
... tures. Principal Component Analysis and Sequential Forward Selection methods are compared in their ability to re- present the feature set in a compact form, removing at the same time unnecessary ...
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Evidence for the role of the diabatic heating in synoptic scale processes: a case study example
... on principal component analysis (PCA) trying to find a daily weather situation, which will most closely resemble the first rotated principal component of the D ...
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Dispositional employability and online training purchase Evidence from employees' behavior in Spain
... using principal component analysis and binomial logit probabilistic models, the research revealed two main ...relationship analysis between dispositional employability and online training ...
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A new rabbit species (Sylvilagus, Mammalia: Leporidae) from the lowlands of Venezuela
... correlation analysis (So- kal & Rohlf 1969), were applied to assay the le- vels of association, differences, and significance ...variations. Principal component analysis (PCA) of the skull ...
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