# News for the SuperLearner package. #


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Version: 2.0-9
Date: 2012-09-10
* Updated help documents
* Added links to SuperLearnerExtra on Github

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Version: 2.0-7
Date: 2012-04-04
* Switched from snow and multicore to parallel package
* fixed bug in CV.SuperLearner for leave-one-out cross-validation
* fixed bug in snowSuperLearner when only one screening algorithm is present
* method.NNloglik now reports the average -log likelihood instead of the sum to be consistent with NNLS

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Version: 2.0-6
Date: 2012-02-29

* Added SL.leekasso (see http://simplystatistics.tumblr.com/post/18132467723/prediction-the-lasso-vs-just-using-the-top-10 for details)
* fixed parallel argument in CV.SuperLearner. Now always a character variable, no longer accepts FALSE.
* fixed SL.gam to call gam::gam.control in case the mgcv package is also loaded after gam.

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Version: 2.0-5
Date: 2011-10-12

* Fixed bug in CV.SuperLearner not saving SuperLearner objects (watch out for ifelse() statements).
* Added minbucket to SL.rpart.
* Added SL.rpartPrune, a version of SL.rpart with built-in pruning.

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Version: 2.0-4
Date: 2011-10-01

* Minor changes to Rd files to cut build and check time. Time intensive examples now wrapped in \dontrun for CRAN.

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Version: 2.0-3
Date: 2011-08-05

* added plot.CV.SuperLearner

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Version: 2.0-2
Date: 2011-06-07

* fixed bug when one of the algorithms in SL.library has an error.
* fixed mcSuperLearner and snowSuperLearner not saving fitLibrary.
* added a placeholder Sweave vignette (SuperLearnerPresent.Rnw) to contain the SuperLearner presentation so the file can be found using the vignette() and browseVignettes() functions.
* CV.SuperLearner now outputs `LibraryNames`, `SL.library`, `method` and `Y`.
* summary.CV.SuperLearner has returned

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Version: 2.0-1  
Date: 2011-05-17

* added predict.SuperLearner


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Version: 2.0-0  
Date: 2010-12-27

* Version 2.* represents a complete rewrite of the SuperLearner package.
* Details on the changes from Version 1.* to 2.* can be found in ChangeLog.