Solving In-Table Prediction Problems by Deep Neural Networks with Performance Evaluation Using Synthetic Data
This work investigates whether NNs can predict the values of arbitrarily selected columns in a given table based on the remaining known columns, and concludes that the attention-based structure outperforms the other two networks, when a sufficiently large number of training examples is available and a relatively large...