Projects supporting the r data format.


Logo XGBoost v0.3.0

by crowwork - September 2, 2014, 02:43:31 CET [ Project Homepage BibTeX Download ] 2673 views, 482 downloads, 2 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily.

Changes:

New features: - R support that is now on CRAN

  • Faster tree construction module

  • Support for boosting from initial predictions

  • Linear booster is now parallelized, using parallel coordinated descent.


Logo JMLR fastclime 1.2.3

by colin1898 - March 10, 2014, 08:54:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1563 views, 393 downloads, 1 subscription

About: The package "fastclime" provides a method of recover the precision matrix efficiently by applying parametric simplex method. The computation is based on a linear optimization solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method.

Changes:

Initial Announcement on mloss.org.


Logo mldata.org svn-r1070-Apr-2011

by sonne - April 8, 2011, 10:15:49 CET [ Project Homepage BibTeX Download ] 3763 views, 704 downloads, 1 subscription

About: The source code of the mldata.org site - a community portal for machine learning data sets.

Changes:

Initial Announcement on mloss.org.


Logo NetPro 1.1.17

by lml - January 25, 2011, 19:02:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3307 views, 785 downloads, 1 subscription

About: Tools for functional network analysis.

Changes:

Initial Announcement on mloss.org.