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Combining Predictive Analytics and Experimental Design to Optimize Results. 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.
Package details |
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Author | Deniz Akdemir |
Maintainer | Deniz Akdemir <deniz.akdemir.work@gmail.com> |
License | GPL-3 |
Version | 5.2.1 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
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