2.2.2 - Techniques to Handle Missing Data
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Practice Questions
Test your understanding with targeted questions
What is the purpose of deletion in handling missing values?
💡 Hint: Think about what happens when you remove data.
Describe mean imputation.
💡 Hint: What do we calculate to find the 'mean'?
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the primary method for filling in small amounts of missing data?
💡 Hint: Think about removing minimal versus large amounts of missing information.
True or False: Mean imputation can introduce bias if the data distribution is skewed.
💡 Hint: Consider how averages behave in skewed distributions.
1 more question available
Challenge Problems
Push your limits with advanced challenges
You have a dataset with 20% missing values in a feature. When considering deletion and imputation, what factors would influence your decision?
💡 Hint: Reflect on the balance between data quantity and quality.
Design an experiment where you use KNN for imputation, outlining your dataset, chosen neighbors, and the method to evaluate accuracy.
💡 Hint: Remember to tune the number of neighbors for optimal performance.
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