R Deep Learning Essentials - Second Edition

Evaluation metrics and evaluating performance

This section will discuss how to set up a deep learning project and what evaluation metrics to select. We will look at how to select evaluation criteria and how to decide when the model is approaching optimal performance. We will also discuss how all deep learning models tend to overfit and how to manage the bias/variance tradeoff. This will give guidelines on what to do when models have low accuracy.