Data Preprocessing Questions
Data imputation using decision trees is a technique used in data preprocessing to fill in missing values in a dataset. It involves using a decision tree algorithm to predict the missing values based on the available data. The decision tree is trained on the dataset with complete data, where the target variable is the attribute with missing values. Once the decision tree is trained, it can be used to predict the missing values by traversing the tree and assigning the most probable value based on the available attributes. This method helps to maintain the integrity and completeness of the dataset for further analysis or modeling.