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High-dimensional statistics
Results: 273

#	Item
231	Biostatistics Advance Access published April 13, 2006 Sample size planning for developing classifiers using high dimensional DNA microarray data Kevin K. Dobbin∗ Add to Reading List Source URL: linus.nci.nih.gov Language: English - Date: 2013-03-12 10:01:26 Data analysis Gene expression Gene expression profiling Variance DNA microarray Covariance matrix Linear discriminant analysis Significance analysis of microarrays Statistics Biology Microarrays
232	High-Dimensional Visual Analytics: Interactive Exploration Guided by Pairwise Views of Point Distributions∗ Leland Wilkinson† Anushka Anand‡ Add to Reading List Source URL: www.cs.uic.edu Language: English - Date: 2010-02-27 00:59:51 Multivariate statistics Plot Outlier Minimum spanning tree Principal component analysis Nearest neighbor graph Robust statistics Cluster analysis Graph Statistics Graph theory Data analysis
233	Fast Approximate k-Means via Cluster Closures∗ Jing Wang† † Peking University Jingdong Wang‡ Qifa Ke§ Gang Zeng† Shipeng Li‡ Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2012-03-30 05:59:51 Cluster analysis Data mining Machine learning Geostatistics K-means clustering Nearest neighbor search Clustering high-dimensional data Consensus clustering Statistics Computational statistics Information science
234	grira-houle-last-icml07-formatted.dvi Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:24:47 Cluster analysis Medoid K-medoids K-means clustering Centroid Hierarchical clustering K-medians clustering Clustering high-dimensional data Statistics Computational statistics Means
235	An Efficient Sparse Metric Learning in High-Dimensional Space via !1 -Penalized Log-Determinant Regularization Guo-Jun Qi [removed] Depart. ECE, University of Illinois at Urbana-Champaign, 405 North Mathews Avenue Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2009-05-18 12:16:51 Matrix theory Matrices Multivariate statistics Linear algebra Data analysis Mahalanobis distance Matrix Multivariate normal distribution Covariance matrix Algebra Statistics Mathematics
236	CARE: Finding Local Linear Correlations in High Dimensional Data Xiang Zhang, Feng Pan, and Wei Wang Department of Computer Science University of North Carolina at Chapel Hill Chapel Hill, NC 27599, USA Add to Reading List Source URL: www.cs.ucla.edu Language: English - Date: 2008-02-10 23:19:52 Singular value decomposition Data analysis Model selection Principal component analysis Feature selection Eigenvalues and eigenvectors Correlation and dependence Regression analysis Linear discriminant analysis Statistics Multivariate statistics Machine learning
237	Clustering Pair-wise Dissimilarity Data into Partially Ordered Sets Jinze Liu, Qi Zhang, Wei Wang, Leonard McMillan, Jan Prins Department of Computer Science University of North Carolina, Chapel Hill, NC 27599 {liuj, zha Add to Reading List Source URL: www.cs.ucla.edu Language: English - Date: 2006-06-17 13:24:20 Clique Clustering high-dimensional data K-means clustering Nearest-neighbor chain algorithm Complete-linkage clustering Statistics Cluster analysis Hierarchical clustering
238	Microsoft Word - handbook_v3.doc Add to Reading List Source URL: www.cs.ucla.edu Language: English - Date: 2005-06-24 16:50:44 Statistical classification Cluster analysis Data analysis Association rule learning Clustering high-dimensional data Support vector machine Curse of dimensionality Linear classifier Oracle Data Mining Statistics Machine learning Data mining
239	REDUS: Finding Reducible Subspaces in High Dimensional Data Xiang Zhang, Feng Pan, and Wei Wang Department of Computer Science University of North Carolina at Chapel Hill Chapel Hill, NC 27599, USA Add to Reading List Source URL: www.cs.ucla.edu Language: English - Date: 2008-08-31 19:01:55 Multivariate statistics Linear algebra Dimension reduction Machine learning Data analysis Nonlinear dimensionality reduction Principal component analysis Feature selection Column space Statistics Algebra Mathematics
240	Effective Linear Discriminant Analysis for High Dimensional, Low Sample Size Data Zhihua Qiao,∗ Lan Zhou† and Jianhua Z. Huang‡ Abstract— In the so-called high dimensional, low sample size (HDLSS) settings, LDA p Add to Reading List Source URL: www.stat.tamu.edu Language: English - Date: 2008-02-29 23:01:57 Data analysis Singular value decomposition Linear discriminant analysis Principal component analysis Eigenvalues and eigenvectors Covariance matrix Support vector machine Linear regression Variance Statistics Multivariate statistics Statistical classification

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