Measuring performance with cross validation

Cross validation is a method that uses training data to provide multiple estimates of model performance. When trying different model types on your data, it is important to study their performance profile to help decide which model type performs consistently well.

In this exercise, you will perform cross validation with your decision tree model workflow to explore its performance.

The training data, loans_training, and your workflow object, loans_dt_wkfl, have been loaded into your session.

แบบฝึกหัดนี้เป็นส่วนหนึ่งของหลักสูตร

Modeling with tidymodels in R

ดูคอร์ส

แบบฝึกหัดเชิงโต้ตอบแบบลงมือทำ

ลองทำแบบฝึกหัดนี้โดยเติมโค้ดตัวอย่างนี้ให้สมบูรณ์

# Create cross validation folds
set.seed(290)
loans_folds <- ___(___, v = ___,
                   strata = ___)

loans_folds

แก้ไขและรันโค้ด