Data Preprocessing Questions
Data imputation using genetic algorithms is a technique used in data preprocessing to fill in missing values in a dataset. It involves using genetic algorithms, which are optimization algorithms inspired by the process of natural selection, to find the most suitable values to replace the missing data. The genetic algorithm creates a population of potential solutions, evaluates their fitness based on certain criteria, and then evolves the population through selection, crossover, and mutation operations to generate better solutions over successive generations. This iterative process continues until a satisfactory imputation of missing values is achieved.