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Building Predictive Models in <i>R</i> Using the <b>caret</b> Package

Max Kühn · Journal of Statistical Software · 2008

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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.

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APA 7

Kühn, M. (2008). Building Predictive Models in R Using the caret Package. https://doi.org/10.18637/jss.v028.i05

MLA

Kühn, Max. "Building Predictive Models in R Using the caret Package." 2008. https://doi.org/10.18637/jss.v028.i05.

Chicago

Kühn, Max. 2008. "Building Predictive Models in R Using the caret Package.". https://doi.org/10.18637/jss.v028.i05.

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Kühn, M. 2008, Building Predictive Models in R Using the caret Package, Journal of Statistical Software, available at: https://doi.org/10.18637/jss.v028.i05 [Accessed 5 Aug. 2026].

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Title
Building Predictive Models in <i>R</i> Using the <b>caret</b> Package
Author / contributors
Max Kühn
Publisher
Journal of Statistical Software
Publication year
2008
Language
English

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