Consensus clustering

Consensus clustering is a method used to determine the most reliable grouping of data points, like customers or genes, by combining multiple clustering results. Instead of relying on a single analysis, it repeatedly groups the data using different settings or methods, then finds common patterns across these results. This process helps identify stable and consistent clusters, providing greater confidence in the identified groups. Essentially, consensus clustering integrates various clustering attempts to give a clearer, more robust picture of how data naturally divides into meaningful groups.