Practice Evaluation Methodologies of AI Models - 12 | 12. Evaluation Methodologies of AI Models | CBSE Class 12th AI (Artificial Intelligence)
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12 - Evaluation Methodologies of AI Models

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does a confusion matrix show?

💡 Hint: Think about how we compare correct versus incorrect predictions.

Question 2

Easy

Define accuracy in the context of model evaluation.

💡 Hint: Consider the total number of correct predictions.

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 a confusion matrix compare?

  • Actual vs. predicted values
  • Training vs. testing data
  • Model parameters vs. performance

💡 Hint: It's primarily focused on predictions.

Question 2

True or False: Accuracy is always a reliable measure of model performance.

  • True
  • False

💡 Hint: Consider scenarios where accuracy may not reflect true performance.

Solve 3 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Suppose you have an imbalanced dataset with 90% negatives and 10% positives. You want to evaluate the model's performance strictly for the positive class. Which metric would you rely on and why?

💡 Hint: Think about the importance of false positives in your evaluation.

Question 2

Design a small experiment where you apply both train-test split and k-fold cross-validation on the same dataset. Discuss the findings regarding model performance using these two methods.

💡 Hint: Consider how data partitions impact learning.

Challenge and get performance evaluation