Create a zero-variance filter
house_sales_df
contains ten continuous variables describing house sales in King County, California. Examples of these variables include square footage, number of rooms, and sales price. You will need to reduce the dimensionality to make the dataset easier to work with and reduce the training time when creating models.
Let's get started with creating a zero-variance filter. The tidyverse
package has been loaded for you.
This exercise is part of the course
Dimensionality Reduction in R
Exercise instructions
- Create a zero-variance filter using
summarize()
andfilter()
and store it inzero_var_filter
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create zero-variance filter
___ <- ___ %>%
___(across(everything(), ~ ___(___, ___ = ___))) %>%
pivot_longer(everything(), names_to = "feature", values_to = "variance") %>%
___(___ == ___) %>%
pull(feature)
zero_var_filter