👉 The concept of "viewiness" in machine learning is a measure used to evaluate how well a model's predictions or classifications align with human judgments. It involves calculating the similarity between the predicted labels and the actual labels, using metrics such as precision, recall, F1-score, or accuracy. Viewiness can be calculated by comparing the predicted labels against the ground truth labels (also known as the true labels) in a specific dataset. This is done to determine how closely the model's predictions align with
