In some broader sense, the epistemological notion of ground truth could apply to any machine-learning approach, if taken to mean the prior understanding of what sorts of patterns the algorithm is trained to search for. The truths being distilled from the data are those consistent with what domain experts—tutors—or quantitative experts—for example, statisticians, mathematicians, and so forth—consider meaningful.
Source: The Ground Truth in Agile Machine Learning | IBM Big Data & Analytics Hub
