To be utilized to select a test data calibrated training population in high dimensional prediction problems and assumes that the explanatory variables are observed for all of the individuals. Once a "good" training set is identified, the response variable can be obtained only for this set to build a model for predicting the response in the test set. The algorithms in the package can be tweaked to solve some other subset selection problems.
|Date of publication||2017-03-02 08:09:19|
|Maintainer||Deniz Akdemir <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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