Building Predictive Models in R Using the caret Package
Max Kuhn
Journal of Statistical Software, 2008, vol. 028, issue i05
Abstract:
The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training and tuning across a wide variety of modeling techniques. It also includes methods for pre-processing training data, calculating variable importance, and model visualizations. An example from computational chemistry is used to illustrate the functionality on a real data set and to benchmark the benefits of parallel processing with several types of models.
Date: 2008-11-10
References: View complete reference list from CitEc
Citations: View citations in EconPapers (257)
Downloads: (external link)
https://www.jstatsoft.org/index.php/jss/article/view/v028i05/v28i05.pdf
https://www.jstatsoft.org/index.php/jss/article/do ... 05/caret_3.45.tar.gz
https://www.jstatsoft.org/index.php/jss/article/do ... ile/v028i05/v28i05.R
https://www.jstatsoft.org/index.php/jss/article/do ... ratum-2014-01-14.txt
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:028:i05
DOI: 10.18637/jss.v028.i05
Access Statistics for this article
Journal of Statistical Software is currently edited by Bettina Grün, Edzer Pebesma and Achim Zeileis
More articles in Journal of Statistical Software from Foundation for Open Access Statistics
Bibliographic data for series maintained by Christopher F. Baum ().