Fig. 3
From: Deep learning decodes species-specific codon usage signatures in Brassica from coding sequences
Over-fitting detection graphs for multiple machine learning models, including Deep Belief Networks, DNN with L2 regularization, Dropout, Leaky ReLU, MLP, RBFN, and Shallow networks. The plotted Train-Val Accuracy Gap across epochs reveals how each model’s performance evolves, highlighting fluctuations or stabilization trends. These patterns help assess the effectiveness of different regularization techniques in mitigating over-fitting, providing insights into model generalization capabilities.
