What is the role of a validation set in supervised learning?
Practice Questions
Q1
What is the role of a validation set in supervised learning?
To train the model
To test the model's performance on unseen data
To tune hyperparameters and prevent overfitting
To visualize data
Questions & Step-by-Step Solutions
What is the role of a validation set in supervised learning?
Step 1: In supervised learning, we train a model using a training set, which contains input data and the correct output.
Step 2: A validation set is a separate part of the data that is not used during training.
Step 3: The validation set helps us check how well the model is performing while we are still training it.
Step 4: We use the validation set to adjust settings called hyperparameters, which can improve the model's performance.
Step 5: By using the validation set, we can see if the model is learning well or if it is just memorizing the training data (this is called overfitting).
Step 6: The goal is to make sure the model works well on new, unseen data, not just the data it was trained on.
