Mastering Python for Finance - Second Edition

Supervised learning

Supervised learning predicts a certain output from given inputs. These pairings of input to output data are known as training data. The quality of the prediction entirely depends on the training data; incorrect training data reduces the effectiveness of the machine learning model. An example is a dataset of transactions with labels identifying which ones are fraudulent, and which are not. A model can then be built to predict whether a new transaction will be fraudulent.

Some common algorithms in supervised learning are logistic regression, the support vector machine, and random forests.