Cluster analysis

What is cluster analysis?
Cluster analysis is a statistical classification method that groups a group of objects or points with similar properties into clusters. It includes a number of different algorithms and methods, all of which are used to group objects of a similar nature into appropriate categories. The aim of the cluster analysis is to organize the observed data into meaningful structures in order to gain further knowledge.

Cluster analysis can be viewed as a tool for exploratory data analysis that aims to sort different objects into meaningful groups so that the degree to which these objects are associated is maximal when they belong to the same group and when at least you Not. Cluster analysis is used to discover hidden structures or relationships within data without the need to explain or interpret that relationship. Essentially, cluster analysis is only used to discover the structures found in data without explaining why those structures or relationships exist.

Cluster analysis is often applied to very simple things without our knowing them, such as food groups in a grocery store or a group of people eating together in a restaurant. In the grocery store, foods are grouped according to their type such as drinks, meat, and products; We can already draw patterns in relation to these groupings.

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