Data Preprocessing Questions
Data imputation using differential evolution is a technique used in data preprocessing to fill in missing values in a dataset. Differential evolution is an optimization algorithm that is applied to find the best possible values for the missing data points based on the available information. It works by iteratively generating candidate solutions and evaluating their fitness using a cost function. The algorithm then updates the candidate solutions based on their fitness, gradually improving the imputed values until a satisfactory solution is obtained. This approach helps to minimize the impact of missing data on subsequent data analysis tasks and ensures a more complete and accurate dataset for further analysis.