ML: K-Means Clustering

K-means is partitional clustering, the method to partition n data points into k partitions. It is a weird term because clustering is partitioning the data. Actually, partitional clustering gets through the whole data from the beginning to find the k partition. On the other hand, hierarchical clustering starts from a single point. Now, let’s look at K-means

K-means

K-means is just finding the k centroid of the clusters. Centroid means the average of each coordinate of data points in the cluster. The initialization of centroids is really important. I will…