Practice Model Evaluation And Validation Techniques (12) - Model Evaluation and Validation

Practice: Model Evaluation and Validation Techniques

Lesson 12Model Evaluation and Validation

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10 questions

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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
4 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Define accuracy in your own words.
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Think about how you measure performance overall.
Question 2.
What is the purpose of using cross-validation?
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Consider how we can split data effectively.
3Question 3.
What does precision measure in a classification task?
- True positives only
- True positives and false negatives
- True positives divided by the sum of true positives and false positives
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Remember how precision relates to the positive predictions made.
4Question 4.
True or False: Overfitting is when a model performs well on unseen data.
- True
- False
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Think about the training vs. testing scenarios.
Question 5.
Given an imbalanced dataset with a class ratio of 95:5, outline a plan to assess the model’s performance effectively.
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Consider impacts of accuracy versus other metrics.
Question 6.
Design an experiment using nested cross-validation to both tune hyperparameters and evaluate a model. Describe your process.
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How do inner and outer loops interact?

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