what does prototype mean in clustering?

Question

I am studying decision trees and machine learning. I have encountered with this word several time. Although, it seems that it not an important concept, I cannot understand this word in machine learning literature. For example:

if the test does not significantly satisfy the criteria, then it creates a leaf and computes the prototype of the instances belonging to the leaf" .

what does prototype in this sentence mean?

According to Wikipedia:

A prototype is an early sample, model, or release of a product built to test a concept or process or to act as a thing to be replicated or learned from.

But it does not make sense.

Answer 1

A prototype is an element of the data space that represents a group of elements. On the context of clustering (e.g. under a leaf), a cluster prototype serves to characterize the cluster, their elements. You can have a look at Cluster analysis: basic concepts and algorithms for instance, taken from Introduction to data mining.

In a more specific acceptation, it denotes an instance of clustering for combined numerical and categorical values, in the spirit of k-means, k-modes, k-medians, see for instance Into the world of clustering algorithms: k-means, k-modes and k-prototypes:

For numerical and categorical data, another extension of these algorithms exists, basically combining k-means and k-modes. It is called k-prototypes.