What are the best imputation techniques?
An example of an AI chatbot conversation about imputation techniques in data analysis.
What are the best imputation techniques for handling missing data?
There are several effective imputation techniques, including mean/mode imputation, k-nearest neighbors, and multiple imputation.
Can you explain how k-nearest neighbors works for imputation?
Sure! K-nearest neighbors (KNN) imputes missing values by finding the 'k' most similar instances and averaging their values.
Are there any drawbacks to using mean imputation?
Yes, mean imputation can reduce variability and may not be suitable for skewed distributions, leading to biased results.
What about multiple imputation? How does it differ?
Multiple imputation creates several different datasets by imputing values multiple times, allowing for better uncertainty estimation.
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