Classification is concerned with building models that separate data into distinct classes. 1These models are built by inputting a set of training data for which the classes are pre-labelled in order for the algorithm to learn from. The model is then used by inputting a different dataset for which the classes are withheld, allowing the model to predict their class membership based on what it has learned from the training set. Well-known classification schemes include decision trees and support vector machines. As this type of algorithm requires explicit class labelling, classification is a form of supervised learning.
Matthew, Mayo. “Machine Learning Key Terms, Explained.” KDnuggets, KDnuggets, 10AD, 2016, https://www.kdnuggets.com/2016/05/machine-learning-key-terms-explained.html (1)