Data Preprocessing Questions
Data imputation using support vector machines is a technique used in data preprocessing to fill in missing values in a dataset. It involves training a support vector machine (SVM) model on the available data with complete information and then using this model to predict the missing values. The SVM model learns patterns and relationships from the existing data and uses them to estimate the missing values based on the characteristics of the other variables. This approach helps to maintain the integrity and completeness of the dataset, allowing for more accurate analysis and modeling.