How do you do kiestering?

Answer 1

K clustering, commonly known as k-means clustering, is a method used to partition a dataset into K distinct groups based on feature similarity. To perform k-means clustering, first, choose the number of clusters (K) and randomly initialize cluster centroids. Then, repeatedly assign each data point to the nearest centroid and update the centroids based on the mean of the assigned points until the assignments no longer change significantly. This process effectively groups the data points into K clusters based on their proximity to the centroids.