Building Predictive Models in R Using the caret Package

被引:6563
作者
Kuhn, Max [1 ]
机构
[1] Pfizer Global R&D, Nonclin Stat, Groton, CT USA
来源
JOURNAL OF STATISTICAL SOFTWARE | 2008年 / 28卷 / 05期
关键词
model building; tuning parameters; parallel processing; R; NetWorkSpaces;
D O I
10.18637/jss.v028.i05
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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 bene fits of parallel processing with several types of models.
引用
收藏
页码:1 / 26
页数:26
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