Practice Use Of Confusion Matrix In Ai (30.5) - Confusion Matrix - CBSE 10 AI (Artificial Intelleigence)

Practice: Use of Confusion Matrix in AI

Lesson 30.5Confusion Matrix

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9 questions

Flashcard drill
2 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does a confusion matrix compare?
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Think about its main purpose!
Question 2.
Why is detecting bias in models important?
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Consider the impact on real-world applications.
3Question 3.
What is the primary purpose of a confusion matrix?
- To visualize model architecture
- To compare predicted results with actual results
- To train new models
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Think about its role in model evaluation.
4Question 4.
True or False: A confusion matrix can help detect biases in machine learning models.
- True
- False
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Consider its function in bias detection.
Question 5.
Given a confusion matrix from a fraud detection model showing 20 true positives, 5 false negatives, 10 false positives, and 65 true negatives, analyze the metrics and suggest improvements.
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Focus on the recall rate and how it may affect financial decisions.
Question 6.
Your model predicts 'Approve' for 90% of loan applications, leading to high accuracy but many rejected applicants. Create metrics to assess model's efficacy.
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Think about the cost of missing legitimate clients.

5 more questions in this section. Enroll free to practise them all.