12.4 - Common Pitfalls in Model Evaluation
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Practice Questions
Test your understanding with targeted questions
Define overfitting in your own words.
💡 Hint: Think about how a student might prepare for an exam.
What is underfitting?
💡 Hint: Consider a model that can only draw straight lines.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is overfitting?
💡 Hint: Think about how a student can 'memorize' the material.
True or False: Data leakage can make a model appear to have a better performance than it truly does.
💡 Hint: Consider how improper mixing of datasets can affect results.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Imagine you are developing a model to predict loan approvals. Discuss potential pitfalls considering the imbalanced nature of approvals versus denials.
💡 Hint: Consider the ratios of approvals to denials.
Design a plan to prevent data leakage during a model training process, detailing your steps.
💡 Hint: Think about all data operations involving separate training and test datasets.
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