Overfitting is a term commonly used in data science and machine learning, but it can also be relevant to the field of catalysis. In catalysis, overfitting refers to a situation where a catalytic system or a predictive model of a catalytic process is too closely tailored to specific data sets or conditions. This can lead to poor generalization and performance when the system is exposed to new data or different reaction conditions.
