Practice Real-Life Example - 28.6 | 28. Introduction to Model Evaluation | CBSE Class 10th AI (Artificial Intelleigence)
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28.6 - Real-Life Example

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define what recall is in the context of model evaluation.

💡 Hint: Think about how many actual spam were caught by the model.

Question 2

Easy

What does precision refer to in evaluating models?

💡 Hint: Consider the accuracy of the positive predictions made by the model.

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 recall?

  • Number of correct positive predictions
  • Proportion of actual positive instances correctly predicted
  • A type of evaluation metric

💡 Hint: It's about how well the model recognizes real spam emails.

Question 2

True or False: A high recall score means the model is performing well.

  • True
  • False

💡 Hint: Consider how many false positives undermine the effectiveness of a model.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

A company wants to enhance its spam detection model to improve the user experience. They notice a shift where user reports of spam emails have doubled. Analyze potential reasons and suggest improvements based on evaluation metrics.

💡 Hint: Look at the balance between true positives and false positives.

Question 2

Given a list of 50 spam emails and 100 legitimate emails, if the model classifies 40 of the spam correctly but labels 20 legitimate emails as spam, calculate precision, recall, and F1 Score.

💡 Hint: Calculate one step at a time for accurate results.

Challenge and get performance evaluation