Pääryhmittely
Pääryhmittely, also known as hierarchical clustering, is a method of cluster analysis which seeks to build a hierarchy of clusters. It is a type of unsupervised learning algorithm used in data mining and machine learning. The goal of pääryhmittely is to group a set of objects in such a way that objects in the same group (called a cluster) are more similar to each other than to those in other groups.
The algorithm starts with each object as its own cluster and then iteratively merges the closest pairs
Pääryhmittely can be represented as a dendrogram, a tree-like diagram that shows the arrangement of the clusters
One of the main advantages of pääryhmittely is that it does not require the number of clusters
Pääryhmittely is widely used in various fields, such as bioinformatics, image analysis, and market research, to