Example Concept: Imputation is a technique used to fill in missing values in a dataset. Simple methods include replacing missing values with the mean, median, or mode of the column, which works well for numerical data with a normal distribution. For more complex datasets, predictive modeling techniques like k-nearest neighbors (KNN) or regression imputation can be used to predict missing values based on other available data. These methods help maintain data integrity and improve model performance by providing a complete dataset for training.