Clustering

Clustering algorithms are unsupervised algorithms and offer a unique solution to problems where finding the closest match to related items is the desired solution. During the training of the data, the data is grouped based on the features, and then during the prediction, the closest match is chosen. Some examples of the use of clustering algorithms include file type classification and predicting customer choices. 

ML.NET uses the k-means algorithm specifically, which we will deep dive into in Chapter 5, Clustering Model.