klusterianalyysillä
Klusterianalyysi, or cluster analysis, is a statistical method used 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. It is an unsupervised learning technique, meaning it does not require pre-labeled data. The primary goal is to discover inherent groupings within the data.
The process typically involves defining a similarity or dissimilarity measure between objects. Common measures include Euclidean
Popular algorithms include k-means, which aims to partition the data into k clusters where each data point
The choice of algorithm and the number of clusters are often determined by the specific problem and