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Principal component analysis
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871	Chapter 4: Formulating the Predictor Variables Chapter 3 focused on the construction of a gridded daily rainfall dataset, which will form the response variable in the statistical model that is the goal of this thesis. Th Add to Reading List Source URL: www.cru.uea.ac.uk Language: English - Date: 2009-12-22 04:43:50 Data analysis Multivariate statistics Singular value decomposition Abstract algebra Linear algebra Principal component analysis Eigenvalues and eigenvectors Covariance matrix Variance Statistics Algebra Mathematics
872	Sensors and Actuators B[removed]±144 A comparative analysis of basic pattern recognition techniques for the development of small size electronic nose Manuele Bicegoa,, Gino Tessarib, Giampietro Tecchiollia,1, Mar Add to Reading List Source URL: profs.sci.univr.it Language: English* - Date: 2011-10-29 17:44:55 Transducers Technology Biosensor Principal component analysis Measurement Sensors Statistics Biotechnology
873	Command Line Interface, Stochastic SVD∗ Contents 1 Background information 1.1 Add to Reading List Source URL: mahout.apache.org Language: English - Date: 2014-03-08 01:22:19 Singular value decomposition Multivariate statistics Numerical linear algebra Matrix theory Principal component analysis Rank Latent semantic analysis Matrix QR decomposition Algebra Linear algebra Mathematics
874	2.13 Rotated principal component analysis [Book, Sect[removed]Fig.: PCA applied to a dataset composed of (a) 1 cluster, (b) 2 clusters, (c) and (d) 4 clusters. In (c), an orthonormal rotation ˜j , (j =1, 2). and (d) an ob Add to Reading List Source URL: www.ocgy.ubc.ca Language: English - Date: 2013-09-03 18:40:48 Multivariate statistics Singular value decomposition Abstract algebra Matrix theory Principal component analysis Eigenvalues and eigenvectors Factor analysis Rotation matrix Orthonormality Algebra Mathematics Linear algebra
875	694 Journal of the American Statistical Association, June 2009 Discussion Boaz NADLER Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2009-06-16 05:02:26 Data analysis Singular value decomposition Covariance and correlation Principal component analysis Linear algebra Eigenvalues and eigenvectors Covariance matrix Matrix Variance Statistics Algebra Multivariate statistics
876	s10044[removed]5ca-web[removed] Add to Reading List Source URL: profs.sci.univr.it Language: English - Date: 2011-10-29 17:48:42 Statistical classification Microarrays Gene expression Support vector machine DNA microarray Kernel methods Principal component analysis Dimension reduction Feature selection Statistics Machine learning Multivariate statistics
877	A Method to Standardize Usability Metrics Into a Single Score Jeff Sauro PeopleSoft, Inc. Denver, Colorado USA [removed] Add to Reading List Source URL: www.measuringu.com Language: English - Date: 2011-08-26 19:26:15 Data analysis Systems psychology Human–computer interaction Factor analysis Principal component analysis Human factors Variance Normal distribution Software quality Statistics Usability Multivariate statistics
878	C:/Papers/SAM_MDL/MDL.dvi Add to Reading List Source URL: www.research.ibm.com Language: English - Date: 2012-08-13 11:38:52 Linear algebra Multivariate statistics Statistical classification Singular value decomposition Abstract algebra Principal component analysis Tikhonov regularization Linear discriminant analysis Large margin nearest neighbor Algebra Statistics Mathematics
879	BIOINFORMATICS ORIGINAL PAPER Vol. 25 no[removed], pages 258–264 doi:[removed]bioinformatics/btn599 Add to Reading List Source URL: profs.sci.univr.it Language: English - Date: 2011-10-29 18:00:39 Science Statistical classification Multivariate statistics Principal component analysis Linear classifier Mass spectrometry software Support vector machine Two-dimensional nuclear magnetic resonance spectroscopy K-means clustering Statistics Nuclear magnetic resonance Spectroscopy
880	Ch.2 Principal component analysis (PCA) Books on PCA by Jolliffe (2002), Preisendorfer[removed]PCA also called empirical orthogonal function (EOF) analysis. 2.1 Geometric approach to PCA [Book, Sect[removed]Dataset with Add to Reading List Source URL: www.ocgy.ubc.ca Language: English - Date: 2013-08-25 01:58:52 Data analysis Singular value decomposition Covariance and correlation Multivariate statistics Linear algebra Principal component analysis Covariance Eigenvalues and eigenvectors Variance Statistics Algebra Mathematics

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