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Principal component analysis
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#	Item
421	R and Data Mining: Examples and Case Studies 1 Yanchang Zhao Add to Reading List Source URL: cran.csie.ntu.edu.tw Language: English - Date: 2013-04-26 09:13:28 Cluster analysis Multivariate statistics K-means clustering Outlier Random forest Anomaly detection Medoid K-medoids Principal component analysis Statistics Data analysis Data mining
422	R and Data Mining: Examples and Case Studies 1 Yanchang Zhao Add to Reading List Source URL: watson.nci.nih.gov Language: English - Date: 2013-04-26 09:13:28 Cluster analysis Multivariate statistics K-means clustering Outlier Random forest Anomaly detection Medoid K-medoids Principal component analysis Statistics Data analysis Data mining
423	Graduate Seminar Online Robust PCA or Online Sparse + Low-Rank Matrix Recovery Dr. Namrata Vaswani Associate Professor, Add to Reading List Source URL: www.ece.cmu.edu Language: English - Date: 2015-02-25 02:10:41 Multivariate statistics Singular value decomposition Signal processing Data analysis Principal component analysis Sparse matrix Compressed sensing Subspace Vector space Algebra Mathematics Linear algebra
424	Using R for Data Analysis and Graphics Introduction, Code and Commentary J H Maindonald Centre for Mathematics and Its Applications, Australian National University. Add to Reading List Source URL: cran.csie.ntu.edu.tw Language: English - Date: 2008-01-23 03:36:16 Estimation theory R Linear regression Principal component analysis Plot Multivariate adaptive regression splines Generalized additive model for location scale and shape Statistics Regression analysis Econometrics
425	R and Data Mining: Examples and Case Studies 1 Yanchang Zhao Add to Reading List Source URL: ftp.heanet.ie Language: English - Date: 2013-04-26 09:13:28 Cluster analysis Multivariate statistics K-means clustering Outlier Random forest Anomaly detection Medoid K-medoids Principal component analysis Statistics Data analysis Data mining
426	R reference card, by Jonathan Baron Parentheses are for functions, brackets are for indicating the position of items in a vector or matrix. (Here, items with numbers like x1 are user-supplied variables.) Miscellaneous Add to Reading List Source URL: cran.biodisk.org Language: English - Date: 2001-02-09 10:33:01 Principal component analysis Singular value decomposition Matrix Spreadsheet Factor analysis Test Statistics Multivariate statistics Data analysis
427	R reference card, by Jonathan Baron Parentheses are for functions, brackets are for indicating the position of items in a vector or matrix. (Here, items with numbers like x1 are user-supplied variables.) Miscellaneous Add to Reading List Source URL: cran.xl-mirror.nl Language: English - Date: 2001-02-09 10:33:01 Principal component analysis Singular value decomposition Matrix Spreadsheet Factor analysis Test Statistics Multivariate statistics Data analysis
428	Notes on the use of R for psychology experiments and questionnaires Jonathan Baron Department of Psychology, University of Pennsylvania Yuelin Li Center for Outcomes Research, Children’s Hospital of Philadelphia ∗ Add to Reading List Source URL: cran.hafro.is Language: English - Date: 2003-09-09 07:42:07 Matrix Euclidean vector Vector space Array data type Array programming R Column space Principal component analysis Algebra Mathematics Linear algebra
429	R reference card, by Jonathan Baron Parentheses are for functions, brackets are for indicating the position of items in a vector or matrix. (Here, items with numbers like x1 are user-supplied variables.) Miscellaneous Add to Reading List Source URL: mirrors.nic.cz Language: English - Date: 2001-02-09 10:33:01 Principal component analysis Singular value decomposition Matrix Spreadsheet Factor analysis Test Statistics Multivariate statistics Data analysis
430	Workshop on Algorithms for Modern Massive Datasets Stanford University and Yahoo! Research The MMDS (modern massive datasets) workshop provides a forum for discussions on massive, high-dimensional, and Add to Reading List Source URL: www.alterlab.org Language: English - Date: 2006-06-22 10:50:40 Matrix theory Numerical linear algebra Singular value decomposition Multivariate statistics Non-negative matrix factorization Principal component analysis Eigendecomposition of a matrix Matrix Rank Algebra Linear algebra Mathematics

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