Practice - Prepare a Suitable Dataset for Ensemble Learning
Practice Questions
Test your understanding with targeted questions
What is the first step in preparing your dataset for ensemble learning?
💡 Hint: Consider what step involves getting familiar with the data.
Name one method for handling missing values.
💡 Hint: Think about common techniques used in data cleaning.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main objective of preparing a suitable dataset for ensemble learning?
💡 Hint: Think about why we prepare data in the first place.
True or False: Feature scaling is not needed for tree-based ensemble methods.
💡 Hint: Consider how tree algorithms make splits.
1 more question available
Challenge Problems
Push your limits with advanced challenges
You are given a dataset that contains 20% missing values in a key feature. How would you decide whether to impute these missing values or drop the entire column?
💡 Hint: Consider the impact of that feature on the predictive power.
Why might you use one-hot encoding versus label encoding when preparing a dataset for a tree-based model?
💡 Hint: Reflect on when each type of encoding is appropriate based on feature characteristics.
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Reference links
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