EvalForward

EvalForward is a technique used in machine learning to assess how well a model can predict new, unseen data. It involves passing test data through the trained model to obtain predictions and then comparing these predictions to the actual results. This process helps evaluate the model’s accuracy and generalization ability, ensuring it performs reliably outside the training data. Essentially, EvalForward provides a snapshot of how well the model is likely to perform when used in real-world scenarios, guiding improvements and ensuring robustness.