Markov Clustering Algorithm

The Markov Clustering Algorithm (MCL) is a method used to identify groups or clusters in data, especially in network-like structures such as social networks or biological data. It simulates flow within a graph by repeatedly expanding and shrinking the probabilities of moving between nodes (points), which accentuates dense regions. Over iterations, nodes that are closely linked remain grouped together, revealing natural clusters. This process helps to find meaningful communities or patterns within complex datasets by highlighting areas of strong interconnection without requiring prior knowledge of the number of clusters.