>Overspecialization of models, often referred to as overfitting in machine learning, is a condition where a model learns the details and noise in the training data so well that it negatively impacts its performance on new, unseen data. This prevents the model from being able to generalize its knowledge effectively.
>Overspecialization of models, often referred to as overfitting in machine learning, is a condition where a model learns the details and noise in the training data so well that it negatively impacts its performance on new, unseen data. This prevents the model from being able to generalize its knowledge effectively.