Feature selection

Results: 571



#Item
481Singular 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

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

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Source URL: www.cs.ucla.edu

Language: English - Date: 2008-02-10 23:19:52
482Randomness / Feature selection / Random permutation / Variance / Sampling / Decision tree learning / Statistics / Resampling / Statistical inference

Quantitative Association Analysis Using Tree Hierarchies Feng Pan 1 , Lynda Yang 1 , Leonard McMillan 1 , Fernando Pardo Manuel de Villena 2 , David Threadgill 2 and Wei Wang 1 1 Department of Computer Science, 2 Departm

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Source URL: www.cs.ucla.edu

Language: English - Date: 2008-12-26 20:05:28
483Multicollinearity / Least squares / Functional data analysis / Feature selection / Logistic regression / Regularization / Statistics / Regression analysis / Linear regression

Generated using version 3.0 of the official AMS LATEX template Robust Variable Selection in Functional Linear Models Jasdeep Pannu

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Source URL: srcos2014.blogs.rice.edu

Language: English - Date: 2014-07-29 14:34:24
484Multivariate statistics / Linear algebra / Dimension reduction / Machine learning / Data analysis / Nonlinear dimensionality reduction / Principal component analysis / Feature selection / Column space / Statistics / Algebra / Mathematics

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

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Source URL: www.cs.ucla.edu

Language: English - Date: 2008-08-31 19:01:55
485Dimension reduction / Statistical classification / Supervised learning / Principal component analysis / Feature selection / Linear discriminant analysis / Pattern recognition / Statistics / Multivariate statistics / Machine learning

Dimensionality Reduction by Local Discriminative Gaussians Nathan Parrish [removed] University of Washington, Department of Electrical Engineering, Seattle, WA[removed]USA Maya R. Gupta

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Source URL: icml.cc

Language: English - Date: 2012-06-07 13:19:50
486Pruning / Feature selection / Statistics

Sample Selection for Maximal Diversity

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Source URL: www.cs.ucla.edu

Language: English - Date: 2007-10-05 13:57:34
487Statistics / Dimension reduction / Feature selection / Model selection

Mining Non-Redundant High Order Correlations in Binary Data 1 Xiang Zhang 1 , Feng Pan 1 , Wei Wang 1 , and Andrew Nobel 2 Department of Computer Science, 2 Department of Statistics and Operations Research

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Source URL: www.cs.ucla.edu

Language: English - Date: 2008-08-13 18:31:33
488Dimension reduction / Feature selection / Statistical classification / Support vector machine / Symbol / Mutual information / Correlation and dependence / Pearson product-moment correlation coefficient / Statistics / Covariance and correlation / Model selection

Discovering Support and Affiliated Features from Very High Dimensions Yiteng Zhai YZHAI 1@ NTU . EDU . SG Mingkui Tan TANM 0097@ NTU . EDU . SG

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Source URL: icml.cc

Language: English - Date: 2012-06-07 13:20:28
489Multivariate adaptive regression splines / Smoothing spline / Spline / Linear regression / Additive model / Akaike information criterion / B-spline / Least squares / Feature selection / Statistics / Regression analysis / Nonparametric regression

Identification of Nonlinear Additive Autoregressive Models Jianhua Z. Huang † The Wharton School, University of Pennsylvania, Philadelphia, USA. Lijian Yang Michigan State University, East Lansing, USA.

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Source URL: www.stat.tamu.edu

Language: English - Date: 2005-10-07 17:56:44
490Econometrics / Mathematical optimization / Lasso / Linear regression / Least absolute deviations / Robust regression / Multicollinearity / Feature selection / Outlier / Statistics / Regression analysis / Robust statistics

A Robust Variable Selection Method for Grouped Data Kristin Lilly and Nedret Billor Auburn University, Department of Mathematics & Statistics, 221 Parker Hall, Auburn University, Alabama[removed]An example of grouped data

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Source URL: srcos2014.blogs.rice.edu

Language: English - Date: 2014-07-30 15:47:32
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