Data Preprocessing Questions
Data imputation using deep belief networks is a technique used in data preprocessing to fill in missing values in a dataset. Deep belief networks (DBNs) are a type of artificial neural network that consists of multiple layers of hidden units. In the context of data imputation, DBNs are trained on the available data to learn the underlying patterns and relationships. Once trained, the DBN can be used to predict the missing values based on the observed data. This approach helps to minimize the impact of missing data on subsequent analysis and modeling tasks.