Clustering

Clustering is a type of unsupervised machine-learning technique, where the objective is to arrive at conclusions based on the patterns found within unlabeled input data. This technique is mainly used to find meaning in the structure of large data in order to draw decisions.

For instance, from a large list of restaurants in a city, it would be useful to segregate the market into subgroups based on the type of food, quantity of clients, and style of experience to offer each cluster a service that's been configured to its specific needs.

Moreover, clustering algorithms divide the data points into n number of clusters so that the data points in the same cluster have similar features, whereas they greatly differ from the data points in other clusters.

Clustering Types

Clustering algorithms can classify data points using a methodology that is either hard or soft. The former designates data points completely to a cluster, whereas the latter method calculates for each data point the probability...