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Topic :: Machine Learning :: Regularized and Shrinkage Methods [Remove This Filter]
License :: OSI Approved :: GNU General Public License (GPL) [Remove This Filter]
Intended Audience :: Developers [Remove This Filter]
Programming Language :: R [Remove This Filter]
2 projects in result set.
0. Clustering using convex fusion penalties - An R/C++ implementation of the clusterpath algorithm described in Hocking et al. 2011, for robust convex clustering using sparsity-inducing fusion penalties.
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- Development Status : 4 - Beta [Filter]
- Intended Audience : Developers (Now Filtering)
- Intended Audience : End Users/Desktop [Filter]
- License : OSI Approved : GNU General Public License (GPL) (Now Filtering)
- Natural Language : English [Filter]
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- Programming Language : C/C\+\+ [Filter]
- Programming Language : Python [Filter]
- Programming Language : R (Now Filtering)
- Topic : Cluster Analysis : Hierarchical Clustering [Filter]
- Topic : Machine Learning : Regularized and Shrinkage Methods (Now Filtering)
- Topic : Optimization [Filter]
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Registered: 2011-05-09 12:56 |
1. 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]
- Development Status : 5 - Production/Stable [Filter]
- Intended Audience : Developers (Now Filtering)
- Intended Audience : End Users/Desktop [Filter]
- License : OSI Approved : GNU General Public License (GPL) (Now Filtering)
- Natural Language : English [Filter]
- Programming Language : R (Now Filtering)
- Topic : Machine Learning : Boosting [Filter]
- Topic : Machine Learning : Model Selection and Validation [Filter]
- Topic : Machine Learning : Regularized and Shrinkage Methods (Now Filtering)
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Registered: 2008-10-30 14:30 |
