K-MEANS GRID

Entering K-Means simulation...
Watch as data nodes are grouped into K clusters
based on proximity to evolving centroids.

Initializing K centroids at random grid coordinates.
These are the initial guesses for cluster centers.

Assignment Phase: Each data node connects to the nearest centroid.
Visualizing cluster membership via energy signature (color).

Update Phase: Centroids recalibrate their position,
moving to the barycenter (mean) of their assigned nodes.

Iteration cycles repeat: Assign -> Update.
Convergence achieved when centroid positions stabilize.