👉 predespair is a concept in computer science and artificial intelligence, which refers to a state where a machine or system has been trained on a large dataset but still fails to achieve an optimal performance. Predespair can be seen as a type of overfitting where the model does not generalize well to new data, leading to poor predictions on unseen data. It is often used in machine learning and deep learning models to prevent overfitting by reducing the complexity of the model to its most basic form
