Centroid (EN)

Architecture

A centroid is the center point or center of mass of a cluster in the K-Means algorithm. It represents the average value of all data points in this cluster and is used as a reference point for assigning new data points. In the iterative process of the K-Means algorithm, the centroids are continuously recalculated to find the optimal cluster structure. The position of the centroids determines the boundaries of the clusters and directly influences the result of the clustering process.

flowchart TD     A[Data points] --> B[K-Means Algorithm]     B --> C{Initialization}     C --> D[Assignment to nearest centroid]     D --> E[Calculation of new centroids]     E --> F{Convergence reached?}     F -->|No| D     F -->|Yes| G[Final clusters]     G --> H[Centroids as cluster representatives]