Building Predictive Models in R Using the caret Package

作者：Max Kühn · 发表于：Journal of Statistical Software · 年份：2008 · DOI：10.18637/jss.v028.i05 · 被引用次数：9527 · 研究领域：Metabolomics and Mass Spectrometry Studies、Data Analysis with R、Spectroscopy and Chemometric Analyses

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.