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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define accuracy in your own words.
💡 Hint: Think about the ratio of correct predictions.
Question 2
Easy
What does True Positive mean?
💡 Hint: Consider what 'positive' means in the context of predictions.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the formula for accuracy?
💡 Hint: Recall this formula when considering the number of true and false predictions.
Question 2
True or False: High accuracy always means a model is performing well.
💡 Hint: Think about how class distribution affects this statement.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
A model has 120 true positives, 80 true negatives, 50 false positives, and 50 false negatives. Calculate its accuracy and determine if the accuracy reflects good model performance given the context of class distribution.
💡 Hint: Reassess the implications of accuracy in light of balanced vs. imbalanced datasets.
Question 2
Design a brief evaluation framework for a model predicting heart disease. Discuss why accuracy might not be your primary metric.
💡 Hint: Think about what happens if a sick person is fails to be identified.
Challenge and get performance evaluation