Software Map

Project Tree

Project Tree

Browse By:

7 projects in result set.

0. ctm - Maximum likelihood and boosting estimators for conditional transformation models.

Development Status : 5 - Production/Stable [Filter]
Environment : Console (Text Based) [Filter]
Intended Audience : End Users/Desktop [Filter]
License : OSI Approved : GNU General Public License (GPL) [Filter]
Natural Language : English [Filter]
Programming Language : R [Filter]
Topic : Biostatistics & Medical Statistics [Filter]
Topic : Machine Learning : Boosting [Filter]
Topic : Regression Models [Filter]

Activity Percentile: 80.00

Registered: 2012-01-12 14:03

1. gbm - Generalized Boosted Models. Adding additional functionality to the gbm package, including additional robust regression methods, a new binomial classification method, and multinomial classification.

Development Status : 5 - Production/Stable [Filter]
Intended Audience : Developers [Filter]
Intended Audience : End Users/Desktop [Filter]
License : OSI Approved : GNU General Public License (GPL) [Filter]
Natural Language : English [Filter]
Operating System : OS Independent [Filter]
Programming Language : C/C\+\+ [Filter]
Programming Language : R [Filter]
Topic : Machine Learning : Boosting [Filter]
Topic : Regression Models [Filter]

Registered: 2009-06-02 16:27

2. mboost - Boosting algorithms for fitting generalized linear, additive and interaction models to potentially high-dimensional data. For an up to date version see https://github.com/boost-R/mboost

Development Status : 5 - Production/Stable [Filter]
Intended Audience : Developers [Filter]
Intended Audience : End Users/Desktop [Filter]
License : OSI Approved : GNU General Public License (GPL) [Filter]
Natural Language : English [Filter]
Programming Language : R [Filter]
Topic : Machine Learning : Boosting [Filter]
Topic : Machine Learning : Regularized and Shrinkage Methods [Filter]
Topic : Multivariate Statistics : Linear Models [Filter]

Registered: 2007-07-07 15:13

3. l2boost - Efficient boosting method using the l2-loss function with gradient descent along coordinate direction basis functions for linear regression.
Development Status : 4 - Beta [Filter] Intended Audience : End Users/Desktop [Filter] Intended Audience : Other Audience [Filter] License : OSI Approved : GNU General Public License (GPL) [Filter] Natural Language : English [Filter] Operating System : OS Independent [Filter] Programming Language : R [Filter] Topic : Machine Learning : Boosting [Filter]	Activity Percentile: 0.00 Registered: 2012-05-01 11:39

4. CoxFlexBoost - CoxFlexBoost: likelihood-based boosting approach to fit structured Cox-type survival models with linear, smooth and (linear/smooth) time-varying effects. By applying a component-wise boosting approach variable selection and model choice are possible.

Development Status : 4 - Beta [Filter]
Development Status : 5 - Production/Stable [Filter]
Intended Audience : Developers [Filter]
Intended Audience : End Users/Desktop [Filter]
License : OSI Approved : GNU General Public License (GPL) [Filter]
Natural Language : English [Filter]
Programming Language : R [Filter]
Topic : Machine Learning : Boosting [Filter]
Topic : Machine Learning : Model Selection and Validation [Filter]
Topic : Machine Learning : Regularized and Shrinkage Methods [Filter]

Registered: 2008-10-30 14:30

5. gamboostLSS - gamboostLSS: Boosting Methods for GAMLSS Models For an up to date version see https://github.com/boost-R/gamboostLSS
Development Status : 4 - Beta [Filter] License : OSI Approved : GNU General Public License (GPL) [Filter] Operating System : OS Independent [Filter] Programming Language : R [Filter] Topic : Machine Learning : Boosting [Filter] Topic : Machine Learning : Regularized and Shrinkage Methods [Filter] Topic : Multivariate Statistics : Modelling Non-Gaussian Data [Filter]	Registered: 2010-06-29 15:27

6. Rule-Based Models - This project contains GPL versions of Quinlan's C5.0 and Cubist models.
Topic : Machine Learning : Boosting [Filter] Topic : Machine Learning : Recursive Partitioning [Filter] Topic : Multivariate Statistics : Supervised Classification and Discriminant Analysis [Filter]	Activity Percentile: 0.00 Registered: 2011-02-25 15:11