Practice Evaluation (8) - Evaluation - CBSE 10 AI (Artificial Intelleigence)

Practice: Evaluation

Lesson 8Evaluation

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9 questions

Flashcard drill
4 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 is evaluation in AI?
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Think about what happens after the model is trained.
Question 2.
What is the training set used for?
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Recall which dataset is fed into the model to learn.
3Question 3.
What is the primary purpose of evaluating an AI model?
- To improve training data
- To assess performance and accuracy
- To select features
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Consider the user experience with the model once it is deployed.
4Question 4.
True or False: Overfitting occurs when a model performs poorly on both training and testing data.
- True
- False
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Think about what happens when it learns too many details.
Question 5.
You have a dataset where you trained an AI to categorize images into two classes: cats and dogs. After evaluation, you found your model’s accuracy is 85%, but the precision is only 70%. What's the potential issue with the model?
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Consider what high accuracy but low precision implies about false classifications.
Question 6.
In a K-Fold cross-validation with k=5, if you trained the model and got different accuracy scores for each fold, what could you conclude about the model’s performance?
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Think about the importance of consistent performance across datasets.

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