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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does PAC stand for?
💡 Hint: Think about the framework's name.
Question 2
Easy
In PAC learning, what do ε and δ represent?
💡 Hint: Recall each parameter's role in determining learnability.
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 does ε represent in PAC learning?
- A measure of confidence
- The desired error bound
- The sample size
💡 Hint: Think of what you want to limit in the predictions.
Question 2
In PAC learning, δ signifies what?
- True - it represents the coefficient of variation
- False - it represents the desired error
💡 Hint: Consider what δ indicates in terms of certainty.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Suppose a machine learning model achieves a 0.05 error rate with a probability of 0.95 on 100 samples. If another model learns a more complex function requiring 300 samples, calculate the expected error rate and confidence level based on PAC learning principles.
💡 Hint: Focus on how increased samples could lead to better performance but assess complexity.
Question 2
If a learning algorithm performs well with ε = 0.01 and δ = 0.01 after 200 samples, what conclusions can be drawn about its performance? Discuss the implications for increasing sample sizes and the corresponding ε.
💡 Hint: Consider how increasing the sample affects the error margin.
Challenge and get performance evaluation