Why do you need to split a machine learning dataset into training data and test data?
A) So you can try two different sets of features
B) To make sure your model is generalized for more than just the training data
C) To allow you to create unit tests in your code
D) So you can use one dataset for a wide model and one for a deep model

Question

Quizplus · Accepted Answer

Splitting a dataset into training and test data ensures that the model is evaluated on unseen data, which helps in assessing its generalization capability beyond the data it was trained on.

Why Do You Need to Split a Machine Learning Dataset