What are the most accurate imputation methods for missing data?
An example of an AI chatbot conversation about imputation methods and their accuracy.
What are the most accurate imputation methods for missing data?
There are several imputation methods, including mean, median, mode, k-nearest neighbors, and multiple imputation. Each has its strengths.
Can you explain how k-nearest neighbors works for imputation?
Sure! K-nearest neighbors (KNN) imputes missing values by finding the 'k' closest data points and averaging their values.
How does the accuracy of KNN compare to other methods?
KNN can be very accurate, especially with large datasets, but it may struggle with high-dimensional data compared to methods like multiple imputation.
What factors should I consider when choosing an imputation method?
Consider the nature of your data, the amount of missingness, and the underlying distribution. It's often useful to test multiple methods.
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