UTILIZATION OF AUTO ENCODERS AS A GENERALIZATION METHOD FOR ANTI-SPOOFING CLASSIFICATION - 528, Er.Vishal Kumar, Ms.Rachna Rajput (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2022)
When training large neural networks, explicit generalisation procedures are required to ensure that the model's predictions can be generalised. Auto-encoders now have a new generalisation result. As a result of the data's limited diversity, generalisation issues arise when developing models aimed at tackling these types of problems. Regularization is often added by including a regularisation parameter in the objective function; however, in this paper, we will provide an alternative regularisation approach that is equal to the one commonly used. The fact that other regularisation strategies failed to eliminate overfitting implies that these regularisation techniques may be used as a pre-processing step for other algorithms.