Automated feature selection caret (fscaret)

This package provide fast and automated feature selection based on caret package modeling methods. The main advantage of this extension is that it requires minimum user involvement. Also the variety of used methods in combination with the scaling according to RMSE or MSE obtained from models profit the user. The idea is based on the assumption that the variety of models will balance the roughness of calculations (default model settings are applied). On Windows OS the time limiting function is off, multicore functionalaity is enabled via parLapply() function of package 'parallel'. Acknowledgments: This work was funded by Poland-Singapore bilateral cooperation project no 2/3/POL-SIN/2012


Package: fscaret
Type: Package
Date: 2017-12-07
License: GPL-2 | GPL-3


Kuhn M. (2008) Building Predictive Models in R Using the caret Package Journal of Statistical Software 28(5) http://www.jstatsoft.org/. Szlek J, Paclawski A, Lau R, Jachowicz R, Mendyk A. Heuristic modeling of macromolecule release from PLGA microspheres. International Journal of Nanomedicine. 2013:8(1); 4601 - 4611. http://www.dovepress.com/international-journal-of-nanomedicine-journal.

See Also

train, trainControl, rfeControl by Max Kuhn <Max.Kuhn at pfizer.com> and predict base utilities

  • fscaret-package
Documentation reproduced from package fscaret, version, License: GPL-2 | GPL-3

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