Supervised learning

Supervised learning is nowadays the most common form of ML applied to business processes. These algorithms try to find a good approximation of the function that is mapping inputs and outputs.

To accomplish that, it is necessary to provide both input values and output values to the algorithm yourself, as the name suggests, and it will try to find a function that minimizes the errors between the predictions and the actual output.

The learning phase is called training. After a model is trained, it can be used to predict the output from unseen data. This phase is commonly regarded as scoring or predicting, which is depicted in the following diagram: