Building Predictive Models in R Using the caret Package
Building Predictive Models in R Using the caret Package
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DOI：
10.18637/jss.v028.i05
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发表时间：
2008-11-01
影响因子：
5.8
通讯作者：
Kuhn, Max
中科院分区：
文献类型：
--
作者：
Kuhn, Max
插入符号包是分类和回归训练的缩写，它包含许多工具，用于使用R中提供的丰富模型集开发预测模型。该包侧重于简化各种建模技术中的模型培训和调整。它还包括对训练数据进行预处理、计算变量重要性和模型可视化的方法。一个来自计算化学的例子被用来说明在真实数据集上的功能，并用几种类型的模型对并行处理的优点进行基准测试。
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.