Preparing the training and testing datasets
Building a classification model requires a training dataset to train the classification model, and testing data is needed to then validate the prediction performance. In the following recipe, we will demonstrate how to split the telecom churn dataset into training and testing datasets, respectively.
Getting ready
In this recipe, we will use the telecom churn dataset as the input data source, and split the data into training and testing datasets.
How to do it...
Perform the following steps to split the churn dataset into training and testing datasets:
- You can retrieve the churn dataset from the
C50
package:> install.packages("C50") > library(C50) > data(churn)
- Use
str
to read the structure of the dataset: ...
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