Creating training and test datasets
The rsample package is designed to create training and test datasets. Creating a test dataset is important for estimating how a trained model will likely perform on new data. It also guards against overfitting, where a model memorizes patterns that exist only in the training data and performs poorly on new data.
In this exercise, you will create training and test datasets from the home_sales data. This data contains information on homes sold in the Seattle, Washington area between 2015 and 2016.
The outcome variable in this data is selling_price.
The tidymodels package will be pre-loaded in every exercise in the course. The home_sales tibble has also been loaded for you.
Diese Übung ist Teil des Kurses
Modeling with tidymodels in R
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
# Create a data split object
home_split <- ___(home_sales,
prop = ___,
strata = ___)