What are advanced imputation techniques for handling missing data?
An example of an AI chatbot conversation about advanced methods for filling in missing data.
What are advanced imputation techniques for handling missing data?
Advanced imputation techniques include methods like multiple imputation, k-nearest neighbors, and regression imputation.
Can you explain multiple imputation in more detail?
Sure! Multiple imputation involves creating several different plausible datasets by filling in missing values multiple times.
How does k-nearest neighbors work for imputation?
K-nearest neighbors (KNN) imputes missing values by finding the 'k' most similar instances and averaging their values.
Are there any drawbacks to these techniques?
Yes, drawbacks include increased computational cost and potential bias if the underlying data is not representative.
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