虚拟变量和预处理 [英] Dummy variables and preProcess

问题描述

我有一个包含一些虚拟变量的数据框，我想将其用作 glmnet 的训练集.

I have a data frame with some dummy variables that I want to use as training set for glmnet.

由于我使用的是 glmnet，我想使用插入符号 train 函数中的 preProcess 选项来居中和缩放特征.我不希望这种转换也应用于虚拟变量.

Since I'm using glmnet I want to center and scale the features using the preProcess option in the caret train function. I don't want that this transformation is applied also to the dummy variables.

有没有办法阻止这些变量的转换?

Is there a way to prevent the transformation of these variables?

推荐答案

除了编写 自定义模型 这样做(参见接近尾声的 PLS 和 RF 示例).

There's not (currently) a way to do this besides writing a custom model to do so (see the example with PLS and RF near the end).

我正在研究一种方法来指定哪些变量获得哪种预处理方法.但是，对于虚拟变量，这很困难，因为您可能需要指定许多列不在当前数据集中的预测变量的名称.我们的想法是能够使用通配符(例如 Species* 来捕获 Speciesversicolor 和 Speciesvirginica)，但代码还没有完成.

I'm working on a method to specify which variables get which pre-processing method. However, with dummy variables, this is tough since you might need to specific the names of a lot of predictors whose columns are not in the current dat set. The idea is to be able to use wildcards (e.g. Species* to capture Speciesversicolor and Speciesvirginica) but the code isn't quite there yet.

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