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2 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.   | 
- Development Status : 4 - Beta (Now Filtering) 
 - Development Status : 5 - Production/Stable [Filter] 
 
- Intended Audience : Developers (Now Filtering) 
 - Intended Audience : End Users/Desktop (Now Filtering) 
 
- License : OSI Approved : GNU General Public License (GPL) (Now Filtering) 
 
- 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] 
 
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 Registered: 2008-10-30 14:30 | 
1. 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.   | 
- Development Status : 4 - Beta (Now Filtering) 
 
- Intended Audience : Developers (Now Filtering) 
 - Intended Audience : End Users/Desktop (Now Filtering) 
 
- License : OSI Approved : GNU General Public License (GPL) (Now Filtering) 
 
- Natural Language : English [Filter] 
 
- Operating System : OS Independent [Filter] 
 
- Programming Language : C/C\+\+ [Filter] 
 - Programming Language : Python [Filter] 
 - Programming Language : R [Filter] 
 
- Topic : Cluster Analysis : Hierarchical Clustering [Filter] 
 - Topic : Machine Learning : Regularized and Shrinkage Methods [Filter] 
 - Topic : Optimization [Filter] 
 
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 Registered: 2011-05-09 12:56 |