ruggedness analysis

Ruggedness analysis is a method used to evaluate how consistently a model's predictions hold up when input data varies slightly. It involves testing the model's performance across different scenarios or slight changes in conditions to see if it remains reliable or becomes unstable. This helps identify whether the model is robust—able to handle real-world variability—or sensitive, which could lead to errors. Essentially, ruggedness analysis ensures that a model can perform well not just in ideal situations but also in diverse, unpredictable environments, increasing trust in its real-world application.