Machine Learning Flashcards
6 cards from real Artificial Intelligence practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Machine Learning flashcards as text
Which type of machine learning uses labeled training data to learn a mapping from inputs to outputs?
Answer: Supervised learning
Supervised learning trains on labeled input-output pairs to predict outputs for new inputs.
What is the purpose of a validation set in machine learning?
Answer: To tune hyperparameters and detect overfitting
The validation set is used during training to tune hyperparameters and monitor for overfitting.
Which metric is most appropriate when classes in a dataset are heavily imbalanced?
Answer: F1 Score
F1 Score balances precision and recall, making it more informative than accuracy on imbalanced datasets.
What does regularization in machine learning primarily address?
Answer: Overfitting
Regularization adds a penalty to the loss function to reduce model complexity and prevent overfitting.
In a decision tree, what does 'pruning' accomplish?
Answer: Removes branches to reduce overfitting
Pruning removes branches that provide little power, simplifying the tree to improve generalization.
What is the 'bias-variance tradeoff' in machine learning?
Answer: The tension between underfitting (high bias) and overfitting (high variance)
The bias-variance tradeoff describes how increasing model complexity reduces bias but increases variance.