This pull request adds a C++ implementation of the K-Means Clustering algorithm, which uses Euclidean distance to group data points based on proximity to centroids. Users can specify the number of clusters, data points, and iterations. After processing, the final centroids and cluster assignments are displayed, providing a foundational tool for clustering analysis.
This pull request adds a C++ implementation of the K-Means Clustering algorithm, which uses Euclidean distance to group data points based on proximity to centroids. Users can specify the number of clusters, data points, and iterations. After processing, the final centroids and cluster assignments are displayed, providing a foundational tool for clustering analysis.