The correct answer is: A. split the set of example into the training set and the test.
Supervised learning is a type of machine learning in which the model is trained on a set of labeled data. The labeled data consists of a set of examples, each of which has a label that indicates the correct output for that example. The model is then trained to learn the relationship between the input data and the output labels.
The standard approach to supervised learning is to split the labeled data into two sets: a training set and a test set. The training set is used to train the model, and the test set is used to evaluate the model’s performance. The model is trained on the training set until it achieves a desired level of performance on the test set.
Option B is incorrect because it does not describe the standard approach to supervised learning. Option C is incorrect because it describes unsupervised learning, not supervised learning. Option D is incorrect because it describes reinforcement learning, not supervised learning.