The first example – the k-means clustering algorithm

The k-means clustering algorithm is a clustering algorithm to group a set of items not previously classified into a predefined number of k clusters. It's very popular within the data mining and machine learning world to organize and classify data in an unsupervised way.

Each item is normally defined by a vector of characteristics or attributes. All the items have the same number of attributes. Each cluster is also defined by a vector with the same number of attributes that represents all the items classified into that cluster. This vector is named the centroid. For example, if the items are defined by numeric vectors, the clusters are defined by the mean of the items classified into that cluster. ...

Get Mastering Concurrency Programming with Java 8 now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.