Fit the baseline model

Now that you have a reusable trainControl object called myControl, you can start fitting different predictive models to your churn dataset and evaluate their predictive accuracy.

You'll start with one of my favorite models, glmnet, which penalizes linear and logistic regression models on the size and number of coefficients to help prevent overfitting.

Bu egzersiz

Machine Learning with caret in R

kursunun bir parçasıdır

Kursu Görüntüle

Egzersiz talimatları

Fit a glmnet model to the churn dataset called model_glmnet. Make sure to use myControl, which you created in the first exercise and is available in your workspace, as the trainControl object.

Uygulamalı interaktif egzersiz

Bu örnek kodu tamamlayarak bu egzersizi bitirin.

# Fit glmnet model: model_glmnet
model_glmnet <- train(
  x = churn_x, 
  y = churn_y,
  metric = "ROC",
  method = ___,
  trControl = ___
)

Kodu Düzenle ve Çalıştır