30.3.1 - Accuracy
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What is the formula for calculating accuracy?
💡 Hint: Think about how many correct predictions you need compared to all predictions.
Why might accuracy be a misleading metric?
💡 Hint: Think about scenarios with many more negative cases.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main formula used to calculate accuracy?
💡 Hint: Remember both positive and negative predictions are included.
True or False: Accuracy can be a reliable metric for all types of data sets.
💡 Hint: Think about how many predictions each class has.
1 more question available
Challenge Problems
Push your limits with advanced challenges
In a scenario with 300 instances: 200 actual negatives and 100 positives, a model predicts 80 positives but incorrectly identifies 30 as negatives. Calculate TP, TN, FP, FN, and accuracy.
💡 Hint: Break down the predictions using the definitions given earlier.
You have a dataset with an extreme imbalance, say 90% negatives and only 10% positives. If your model predicts 95% correctly but misses most positives, discuss the implications of this accuracy.
💡 Hint: Consider what accuracy alone fails to explain in performance.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.