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Gradient boosting
Results: 83

#	Item
51	Structure Learning with Hidden Data in Relational Domains Tushar Khot, Sriraam Natarajan∗ , Kristian Kersting∗+ , Jude Shavlik University of Wisconsin-Madison, USA ∗ Wake Forest University School of Medicine, USA Add to Reading List Source URL: first-mm.informatik.uni-freiburg.de Language: English - Date: 2012-07-18 16:57:18 Model theory Statistical models Ensemble learning Gradient boosting Expectation–maximization algorithm Function First-order logic Regression analysis Supervised learning Statistics Mathematics Machine learning
52	Structure Learning with Hidden Data in Relational Domains Tushar Khot, Sriraam Natarajan∗ , Kristian Kersting∗+ , Jude Shavlik University of Wisconsin-Madison, USA ∗ Wake Forest University School of Medicine, USA Add to Reading List Source URL: www.first-mm.eu Language: English - Date: 2012-07-18 16:57:18 Model theory Statistical models Ensemble learning Gradient boosting Expectation–maximization algorithm Function First-order logic Regression analysis Supervised learning Statistics Mathematics Machine learning
53	Lifted Parameter Learning in Relational Models Babak Ahmadi1 [removed] Kristian Kersting1,2,3 [removed] Add to Reading List Source URL: first-mm.informatik.uni-freiburg.de Language: English - Date: 2012-07-18 13:16:28 Theoretical computer science M-estimators Stochastic optimization Estimation theory Stochastic gradient descent Markov logic network Conditional random field Gradient boosting Maximum likelihood Statistics Machine learning Probability and statistics
54	Package ‘CoxBoost’ July 2, 2014 Version 1.4 Title Cox models by likelihood based boosting for a single survival endpoint or competing risks Author Harald Binder Maintainer Harald Binder Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 09:38:46 Machine learning Cross-validation Model selection Degrees of freedom Proportional hazards models Gradient boosting Boosting Null Matrix Statistics Regression analysis Ensemble learning
55	Package ‘ada’ July 2, 2014 Version[removed]Date[removed]Title ada: an R package for stochastic boosting Author Mark Culp, Kjell Johnson, and George Michailidis Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 11:11:47 Statistics Machine learning Data types Boosting Ada Is functions Plot Gradient boosting Array data type Computing Ensemble learning Software engineering
56	Model-based Boosting in R A Hands-on Tutorial Using the R Package mboost Benjamin Hofner∗† Andreas Mayr† Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-10-02 11:30:58 Econometrics Decision trees Actuarial science Gradient boosting Boosting Linear regression Least squares Generalized linear model Multicollinearity Statistics Regression analysis Ensemble learning
57	Package ‘ModelMap’ July 2, 2014 Type Package Title Creates Random Forest and Stochastic Gradient Boosting Models,and applies them to GIS .img files to build detailed prediction maps. Version[removed] Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 10:05:39 Learning Gradient boosting Random forest Null Boosting Statistics /dev/null Ensemble learning Decision trees Artificial intelligence
58	mboost Illustrations Torsten Hothorn1 and Peter B¨ uhlmann2 1 Institut f¨ Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-10-02 11:30:58 Linear regression Logistic regression Proportional hazards models Gradient boosting Least squares Boosting Cross-validation Linear least squares Bootstrapping Statistics Regression analysis Akaike information criterion
59	Package ‘mboost’ October 2, 2014 Title Model-Based Boosting Version[removed]Date[removed]Description Functional gradient descent algorithm Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-10-02 11:30:58 Ensemble learning Statistical methods Mathematical optimization Smoothing spline Gradient boosting Null Matrix Least squares B-spline Statistics Regression analysis Splines
60	ModelMap: an R Package for Model Creation and Map Production Elizabeth A. Freeman, Tracey S. Frescino, Gretchen G. Moisen April 15, 2014 Abstract The ModelMap package (Freeman, 2009) for R (R Development Core Team, 2008) Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-02 10:05:39 Statistical models Decision trees Econometrics Regression model validation Random forest Gradient boosting Boosting Economic model Linear regression Statistics Regression analysis Ensemble learning

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