K-Nearest Neighbors

K-Means Clustering is an unsupervised machine learning algorithm used to partition data into K distinct groups. It begins with randomly selecting K centroids and iteratively assigns each data point to the nearest centroid, then recalculates centroids based on current cluster members. This process continues until convergence, minimizing the variance within each cluster to reveal natural data groupings.