Supervised learning is a machine learning technique that aims to program a computer system so that it can resolve the relevant tasks automatically. To do this, the input data is included in a set I (typically vectors). Then the set of output data is fixed as set O, and finally it defines a function f that associates each input with the correct answer. Such information is called a training set.
These types of algorithms are based on learning by example theory: knowledge is gained by starting from a set of positive examples, which are instances of the concept to be learned, and negative examples, which are non-instances of the concept. In other words, there is a teacher who shows what is right and what is wrong; based on ...
