R: Data Analysis and Visualization

Machine learning

The data to which a ML algorithm is applied is called a training set, which consists of a set of pairs (x, y), called training examples. The pairs are explained as follows:

• x: This is a vector of values, often called the feature vector. Each value, or feature, can be categorical (values are taken from a set of discrete values, such as {S, M, L}) or numerical.
• y: This is the label, the classification or regression values for x.

The objective of the ML process is to discover a function that best predicts the value of y associated with each value of x. The type of y is in principle arbitrary, but there are several common and important ...