validation set

A validation set is a portion of data used during model development to evaluate how well a machine learning model performs on unseen data. After training the model on the training set, the validation set helps tune parameters and select the best version of the model, ensuring it generalizes well to new data. Think of it as a testing ground during development, guiding adjustments to improve accuracy and prevent overfitting. Once optimized with the validation set, the model is typically tested further on a separate test set before deployment.