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.

Este ejercicio forma parte del curso

Dimensionality Reduction in R

Ver curso

Instrucciones del ejercicio

Create a zero-variance filter using summarize() and filter() and store it in zero_var_filter.

Ejercicio interactivo práctico

Prueba este ejercicio y completa el código de muestra.

# Create zero-variance filter
___ <- ___ %>% 
  ___(across(everything(), ~ ___(___, ___ = ___))) %>% 
  pivot_longer(everything(), names_to = "feature", values_to = "variance") %>% 
  ___(___ == ___) %>% 
  pull(feature)

zero_var_filter

Editar y ejecutar código