Multiple feature engineering steps

The power of the recipes package is that you can include multiple preprocessing steps in a single recipe object. These steps will be carried out in the order they are entered with the step_*() functions.

In this exercise, you will build upon your feature engineering from the last exercise. In addition to removing correlated predictors, you will create a recipe object that also normalizes all numeric predictors in the telecommunications data.

The telecom_training and telecom_test datasets have been loaded into your session.

แบบฝึกหัดนี้เป็นส่วนหนึ่งของหลักสูตร

Modeling with tidymodels in R

ดูคอร์ส

แบบฝึกหัดเชิงโต้ตอบแบบลงมือทำ

ลองทำแบบฝึกหัดนี้โดยเติมโค้ดตัวอย่างนี้ให้สมบูรณ์

# Specify a recipe object
telecom_norm_rec <- ___ %>% 
  # Remove correlated variables
  ___ %>% 
  # Normalize numeric predictors
  ___

แก้ไขและรันโค้ด