Subdividing supervised machine learning

Supervised machine learning can be further subdivided into exercises that involve either of the following:

• Classification
• Regression

The concepts are quite straightforward.

Classification involves a machine learning task that has a discrete outcome - a categorical outcome. All nouns are categorical variables, such as fruits, trees, color, and true/false.

The outcome variables in classification exercises are also known as discrete or categorical variables.

Some examples include:

• Identifying the fruit given size, weight, and shape
• Identifying numbers given a set of images of numbers (as shown in the earlier chapter)
• Identifying objects on the streets
• Identifying playing cards as diamonds, spades, hearts and clubs
• Identifying the class rank of a student based on the student's grade
• The last one might not seem obvious, but a rank, that is, 1^st, 2^nd, 3^rd denotes a fixed category. A student could rank, say, 1^st or 2^nd, but not have a rank of 1.5!

Images of some atypical...