In supervised learning, what is the difference between features and labels?

Question

Data Science with Python — Easy

In supervised learning, what is the difference between features and labels?

Accepted Answer

In supervised learning, features are the input variables that the model uses to make predictions, while labels are the target output values that the model learns to predict. This distinction is crucial for training accurate machine learning models.