Supervised Learning

(23rd-May-2020)

• An abstract definition of supervised learning is as follows. Assume the learner is given the following data:

a set of input features, X1,...,Xn;

a set of target features, Y1,...,Yk;

a set of training examples, where the values for the input features and the target features are given for each example; and

• a set of test examples, where only the values for the input features are given.

• The aim is to predict the values of the target features for the test examples and as-yet-unseen examples. Typically, learning is the creation of a representation that can make predictions based on descriptions of the input features of new examples.