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Principal component analysis
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811	CUR from a Sparse Optimization Viewpoint Jacob Bien∗ Department of Statistics Stanford University Stanford, CA 94305 Add to Reading List Source URL: www.cs.yale.edu Language: English - Date: 2010-10-28 23:49:43 Numerical linear algebra Mathematical optimization Multivariate statistics Matrix theory Principal component analysis Sparse approximation Sparse matrix Singular value decomposition Matrix Algebra Mathematics Linear algebra
812	Statistical Inference and Learning- Ex-4 Jonathan Rosenblatt and Boaz Nadler due Feb. 15, 2015 Q1 A continuous time Martingale is a stochastic process defined as follows. Let X(t) be a sequence of random variables with a Add to Reading List Source URL: www.wisdom.weizmann.ac.il Language: English - Date: 2015-01-29 08:44:15 Covariance and correlation Data analysis Singular value decomposition Matrices Probability theory Covariance Principal component analysis Martingale Eigenvalues and eigenvectors Statistics Algebra Mathematics
813	11th International Society for Music Information Retrieval Conference (ISMIRSPARSE MULTI-LABEL LINEAR EMBEDDING WITHIN NONNEGATIVE TENSOR FACTORIZATION APPLIED TO MUSIC TAGGING Yannis Panagakis∗ Constantine Kot Add to Reading List Source URL: ismir2010.ismir.net Language: English - Date: 2014-01-23 13:05:30 Tensors Multilinear algebra Tensor Multilinear subspace learning Principal component analysis Homogeneous polynomial Outer product Rank Information retrieval Algebra Linear algebra Mathematics
814	Proceedings of the 3rd INFORMS Workshop on Data Mining and Health Informatics (DM-HIJ. Li, D. Aleman, R. Sikora, eds. AN INFORMATION VISUALIZATION APPROACH TO CLASSIFICATION AND ASSESSMENT OF DIABETES RISK IN PRIM Add to Reading List Source URL: www.cs.cmu.edu Language: English - Date: 2008-10-22 16:38:12 Nutrition Linear discriminant analysis Principal component analysis Logistic regression Diabetes mellitus Data analysis Low-density lipoprotein Framingham Risk Score Statistics Multivariate statistics Statistical classification
815	Principal Components Analysis - SPSS In principal components analysis (PCA) and factor analysis (FA) one wishes to extract from a set of p variables a reduced set of m components or factors that accounts for most of th Add to Reading List Source URL: core.ecu.edu Language: English - Date: 2014-12-10 19:44:31 Data analysis Covariance and correlation Singular value decomposition Factor analysis Principal component analysis Varimax rotation Eigenvalues and eigenvectors Variance Linear regression Statistics Multivariate statistics Regression analysis
816	The Astronomical Journal, 147:110 (15pp), 2014 May Cdoi: Add to Reading List Source URL: www.stat.berkeley.edu Language: English - Date: 2014-06-25 12:30:09 Extinction Sloan Digital Sky Survey Redshift Astronomical spectroscopy Galaxy Star Principal component analysis Quasar Astronomy Observational astronomy Space
817	MLPACK: A Scalable C++ Machine Learning Library Ryan R. Curtin Neil P. Slagle Add to Reading List Source URL: www.mlpack.org Language: English - Date: 2015-04-03 13:12:33 Free statistical software Data analysis Shogun Weka Non-negative matrix factorization Principal component analysis K-nearest neighbor algorithm Nonlinear dimensionality reduction Application programming interface Statistics Machine learning Multivariate statistics
818	A Method to Standardize Usability Metrics Into a Single Score Jeff Sauro PeopleSoft, Inc. Denver, Colorado USA 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
819	12825-Ballings_VandenPoel Add to Reading List Source URL: www.feb.ugent.be Language: English - Date: 2013-01-08 02:30:54 Statistical classification Kernel trick Kernel Random forest Support vector machine Linux kernel Kernel principal component analysis Kernel adaptive filter Machine learning Statistics Mathematics
820	IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 62, NO. 4, FEBRUARY 15, Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds Add to Reading List Source URL: web.media.mit.edu Language: English - Date: 2014-01-23 05:01:21 Multivariate statistics Data analysis Cluster analysis Graph Spectral graph theory Adjacency matrix Principal component analysis Consensus clustering Clustering high-dimensional data Statistics Mathematics Graph theory

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