KMeans Clustering AI & ML Agent allows you to group similar items in the form of clusters. The number of groups is represented by K. It is a type of unsupervised learning.
In KMeans Clustering the clusters are positioned as points and all data points are associated with the nearest cluster, computed, adjusted and then the process starts over again with new adjustments until the desired result is reached.
K points are placed into the object data space representing the initial group of centroids.
Each object or data point is assigned to the closest k.
The positions of the k centroids are recalculated.
Steps 2 and 3 are repeated until the positions of the centroids no longer move.