K-means: Revision history

Diff selection: Mark the radio buttons of the revisions to compare and hit enter or the button at the bottom.
Legend: (cur) = difference with latest revision, (prev) = difference with preceding revision, m = minor edit.

13 June 2024

  • curprev 11:4511:45, 13 June 2024‎ Ai talk contribs‎ 4,722 bytes +4,722‎ Created page with "== Introduction == K-means is a widely used clustering algorithm in data mining and machine learning. It partitions a dataset into K distinct, non-overlapping subsets or clusters. Each cluster is represented by its centroid, which is the mean of the points within the cluster. The algorithm aims to minimize the sum of squared distances between the data points and their corresponding cluster centroids. This article delves into the intricacies of the K-means algorithm, its..."
Retrieved from "https://canonica.ai/page/K-means"