Practice Accuracy - 8.3 | Chapter 8: Model Evaluation Metrics | Machine Learning Basics
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Accuracy

8.3 - Accuracy

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Practice Questions

Test your understanding with targeted questions

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.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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