Cross-validation

Results: 663



#Item
441Statistical inference / Fraud / Statistical models / Cross-validation / Data mining / Phone fraud / Neural network / Overfitting / Regression model validation / Statistics / Machine learning / Regression analysis

Improper Payment Detection in Department of Defense Financial Transactions1 Dean Abbott Abbott Consulting San Diego, CA [removed]

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Source URL: www.abbottanalytics.com

Language: English - Date: 2010-08-10 08:15:57
442Statistical inference / Cross-validation / Model selection / Regression analysis / Null / Bootstrapping / Is functions / Fold / Mathematical model / Statistics / Mathematics / Machine learning

Package ‘gamclass’ August 23, 2014 Type Package Title Functions and data for a course on modern regression and classification Version 0.55 Date[removed]

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Source URL: cran.r-project.org

Language: English - Date: 2014-08-23 01:39:13
443Econometrics / Estimation theory / Multivariate statistics / Bootstrapping / Linear discriminant analysis / Glaucoma / Cross-validation / Estimator / Resampling / Statistics / Statistical inference / Computational statistics

ipred : Improved Predictors This short manual is heavily based on Peters et˜al. (2002b) and needs some improvements. 1

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Source URL: cran.r-project.org

Language: English - Date: 2014-07-02 12:12:12
444Validation / Medicine / American Red Cross / Government / Electronic signature / Quality management system / Pharmaceutical industry / Technology / Title 21 CFR Part 11

American Red Cross + April 24,2003

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Source URL: www.fda.gov

Language: English - Date: 2004-04-26 10:50:53
445Pharmaceuticals policy / Title 21 CFR Part 11 / United States administrative law / Technology / Government / Medicine / Electronic signature / Validation / Quality management system / Pharmaceutical industry / Computer law / Food and Drug Administration

American Red Cross December 3,2002 Dockets Management Branch (HFA-305)

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Source URL: www.fda.gov

Language: English - Date: 2003-02-04 18:42:15
446Genetics / Microarrays / Bioinformatics / DNA / Molecular genetics / Gene expression profiling / Cross-validation / DNA microarray / Ridge / Biology / Statistics / Gene expression

COMMENTARY Pitfalls in the Use of DNA Microarray Data for Diagnostic and Prognostic Classification Richard Simon, Michael D. Radmacher, Kevin Dobbin, Lisa M. McShane DNA microarrays have made it possible to estimate the

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Source URL: linus.nci.nih.gov

Language: English - Date: 2013-03-12 10:01:29
447Gene expression / Biochemistry / Machine learning / DNA / Molecular genetics / Gene expression profiling / Significance analysis of microarrays / Cross-validation / DNA microarray / Biology / Microarrays / Statistics

ARTICLE Critical Review of Published Microarray Studies for Cancer Outcome and Guidelines on Statistical Analysis and Reporting Alain Dupuy, Richard M. Simon

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Source URL: linus.nci.nih.gov

Language: English - Date: 2013-03-12 10:01:26
448Information science / Data mining / Natural language processing / Statistical inference / Cross-validation / Random forest / Subject / Document classification / Confidence interval / Statistics / Science / Machine learning

A Method of Automated Nonparametric Content Analysis for Social Science Daniel J. Hopkins Georgetown University Gary King Harvard University The increasing availability of digitized text presents enormous opportunities f

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Source URL: gking.harvard.edu

Language: English - Date: 2013-01-10 13:55:33
449Singular value decomposition / Statistical inference / Linear discriminant analysis / Statistical classification / Principal component analysis / Feature selection / Cross-validation / Matrix / Statistical hypothesis testing / Statistics / Multivariate statistics / Model selection

Package ‘hddplot’ July 2, 2014 Type Package Title Use known groups in high-dimensional data to derive scores for plots Version 0.56 Date[removed]

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Source URL: cran.r-project.org

Language: English - Date: 2014-07-02 12:06:59
450Artificial intelligence / Image processing / Machine learning / Object recognition / Linear discriminant analysis / Cross-validation / Template matching / One-shot learning / Boosting methods for object categorization / Computer vision / Statistics / Vision

Joint Feature Selection for Object Detection and Recognition Jerod J. Weinman, Allen Hanson, and Erik Learned-Miller {weinman,hanson,elm}@cs.umass.edu Department of Computer Science University of Massachusetts-Amherst Am

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Source URL: vis-www.cs.umass.edu

Language: English - Date: 2008-01-02 15:36:37
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