Sequence Prediction Using Neural Network Classiers
Proceedings of The 13th International Conference on Grammatical Inference, PMLR 57:164-169, 2017.
Being able to guess the next element of a sequence is an important question in many fields. In this paper we present our approaches used in the Sequence Prediction ChallengE (SPiCe), whose goal is to compare the different approaches to that problem on the same datasets. We model sequence prediction as a classification problem and adapt three different neural network models to tackle it. The experimental results show that our neural network based approaches produce better overall performance than the baseline approaches provided in the competition. In the actual competition, we won the second place using these approaches.