In almost all real-world applications, however, we have to work by induction, inferring the structure from the available evidence. You are most likely to overfit a model when the data is limited and noisy and when your understanding of the fundamental relationships is poor; both circumstances apply in earthquake forecasting. If we either don’t know or don’t care about the truth of the relationship, there are lots of reasons why we may be prone to overfitting the model.
