Data Science, Machine Learning, Programming, Data Analysis, K Means Clustering.
closest centroid. K-Means minimizes the sum of SSE by optimally iteratively moving the centroids. In a way, K-means works by creating a hard partition in the dataset, which act as the cluster boundaries. For example — Fig. 3. The centre cluster is named cluster-one (C1). Original image. In this