Model Performance Metrics Quiz

Quiz covering Model Evaluation and Selection

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

1. 1

   In a binary classification task, which metric represents the proportion of actual positive cases that were correctly identified by the model?

2. 2

   You are training a regression model on Azure Machine Learning to predict housing prices. Which metric is most appropriate if you want to penalize large errors more heavily than small ones?

3. 3

   When evaluating a classification model where the classes are highly imbalanced (e.g., 99% negative, 1% positive), which metric is likely to be the most misleading regarding model performance?

4. 4

   What does the Area Under the ROC Curve (AUC-ROC) score represent in a binary classification model?

5. 5

   During hyperparameter tuning in Azure Machine Learning, you observe that your model has a very low training error but a very high validation error. Which phenomenon is this indicative of?