MLPs for CTR
In this exercise, you will evaluate both the accuracy score and AUC of the ROC curve for a basic MLP model on the ad CTR dataset. Remember to standardize the features before splitting into training and testing!
X
is available as the DataFrame with features, and y
is available as a DataFrame with target values. Both sklearn
and pandas
as pd
are also available in your workspace.
This exercise is part of the course
Predicting CTR with Machine Learning in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Scale features and split into training and testing
X_scaled = ____().____(X)
X_train, X_test, y_train, y_test = ____(
X_scaled, y, test_size = .2, random_state = 0)