When you train your machine to learn, we have to give it a statistically significant random sample as training data. If the training set is not random, we run into the risk of machine learning the patterns which doesn't exist. Also if the training set is too small, the machine will not learn enough and may even reach inaccurate conclusions. Investigate the given example and identify the type of learning. A. Unsupervised learning B. Protocol learning C. Data Learning D. Supervised learning