Practice - Variance
Practice Questions
Test your understanding with targeted questions
What is the main consequence of high variance in a model?
💡 Hint: Think about how a model behaves with lots of complexity.
Define overfitting in your own words.
💡 Hint: Consider how a model's training affects its performance elsewhere.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does high variance in a model indicate?
💡 Hint: Consider how a model performs on new data.
True or False: A model with high variance will perform consistently well on both training and test data.
💡 Hint: Think about performance on new vs. known datasets.
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Challenge Problems
Push your limits with advanced challenges
You are given two datasets: Dataset A is very complex with many outliers, and Dataset B is simple. If you apply a high-degree polynomial model to both datasets and observe the results, discuss how the model's variance would behave differently with each dataset. What could you conclude about model selection?
💡 Hint: Consider how noise in the data influences fitting.
Design a comprehensive strategy to address overfitting you've observed in a model fit to a dataset. Include approaches related to data, model complexity, and evaluation.
💡 Hint: Think broadly about the steps involving the entire modeling process.
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Reference links
Supplementary resources to enhance your learning experience.