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3 projects in result set.
0. 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.
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- Development Status : 4 - Beta [Filter]
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- License : OSI Approved : GNU General Public License (GPL) [Filter]
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- 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]
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Registered: 2008-10-30 14:30 |
1. 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
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- Development Status : 5 - Production/Stable (Now Filtering)
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- 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]
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Registered: 2007-07-07 15:13 |
2. gbm - Generalized Boosted Models. Adding additional functionality to the gbm package, including additional robust regression methods, a new binomial classification method, and multinomial classification.
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- Development Status : 5 - Production/Stable (Now Filtering)
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- Programming Language : R [Filter]
- Topic : Machine Learning : Boosting [Filter]
- Topic : Regression Models [Filter]
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Registered: 2009-06-02 16:27 |
