Cluster Analysis

Cluster analysis is an unsupervised learning method that organises related data points into groups based on shared attributes. This technique identifies underlying patterns in datasets without prior labelling, focusing on maximising internal similarity among items within a cluster while maintaining clear distinctions between different clusters. It is used across various disciplines to uncover hidden structures and inform decision-making processes. The methodology employs algorithms to evaluate similarities and differences, ensuring that elements within a cluster exhibit greater similarity than those in other clusters.