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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the formula for calculating accuracy?
💡 Hint: Think about how correct predictions are comprised.
Question 2
Easy
Can accuracy be misleading? Why?
💡 Hint: Consider a scenario where one class dominates the dataset.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the formula for accuracy?
- (TP + TN) / Total
- (TP + TN) / (TP + FN)
- (TP + TN + FP) / Total
💡 Hint: Think about the correct predictions versus all observations.
Question 2
True or False: Accuracy can effectively evaluate models in imbalanced datasets.
- True
- False
💡 Hint: Consider how class distribution can skew the metrics.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Imagine a situation where you have a model with an accuracy of 97%, but 90% of the data goes to a trivial class. Discuss the implications.
💡 Hint: Consider the balance between the classes in your evaluation.
Question 2
Evaluate a model with the following confusion matrix:
TP = 200, TN = 50, FP = 10, FN = 5. Calculate the accuracy and discuss whether it's a reliable metric.
💡 Hint: Compute accurately, then reflect on class distributions.
Challenge and get performance evaluation