ROC curves and Precision-Recall curves were generated for the neural network, supplying insights into its classification performance, especially in scenarios where imbalanced classes exist. These visualization techniques helped not only an assessment of model performance but also a deeper understanding of where the models excelled and where improvements could be made. They contributed to the interpretability of our PPI prediction models, making them more accessible and informative to researchers and domain experts.