We are going to start with an unsupervised learning algorithm that goes by the name of k-means clustering. As the name suggests, k-means clustering is a type of a more generic class of clustering algorithms. So, what do we understand by clustering?
Clustering does what you would expect it to do-group together similar objects (similar in meaning to what the English word clustering implies). What do you mean by similar objects and how exactly does it perform the grouping? We will answer these questions in detail in this and the following sections.
Like before, we will motivate the basic concept behind k-means clustering by showing examples of what kind of data it operates on and what it does. Let's say that we have a sufficiently large class of students. We want to divide them into three separate groups for the purpose of some academic activity. We want the group division to happen on the basis of the marks that they obtained in the most recent exams. For each...
