Distribution of outcome variable values
Stratifying by the outcome variable when generating training and test datasets ensures that the outcome variable values have a similar range in both datasets.
Since the original data is split at random, stratification avoids placing all the expensive homes in home_sales
into the test dataset, for example. In this case, your model would most likely perform poorly because it was trained on less expensive homes.
In this exercise, you will calculate summary statistics for the selling_price
variable in the training and test datasets. The home_training
and home_test
tibbles have been loaded from the previous exercise.
Cet exercice fait partie du cours
Modeling with tidymodels in R
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Distribution of selling_price in training data
___ %>%
summarize(min_sell_price = ___,
max_sell_price = ___,
mean_sell_price = ___,
sd_sell_price = ___)