AI, Machine Learning, Unsupervised Learning.
nearest cluster centroid and updates the centroids until convergence. Tries to minimize the sum of squared distances between data points and their assigned cluster centroids. Applications: Customer segmentation and image compression. 2. Hierarchical clustering Can be used to build a hierarchy of