Data Preprocessing Questions
Data imputation using multiple imputation is a technique used in data preprocessing to handle missing values in a dataset. It involves creating multiple plausible imputations for the missing values based on the observed data. Each imputation is generated using statistical models and algorithms, taking into account the relationships and patterns present in the dataset. By creating multiple imputations, the uncertainty associated with the missing values is captured, allowing for more accurate and reliable analysis. The imputed values are then used in subsequent data analysis tasks.