Ground truth is a term commonly used in statistics and machine learning. It signifies the correct or “true” answer to a specific problem or question. Each ML model makes predictions to values or boolean classifications about a problem. Each time the ML model's prediction or classification is compared to the ground truth, which is what is expected to be the correct answer, based on real data in the dataset.
