K-means Clustering

In this chapter, we explore the K-means clustering algorithm, emphasizing an accessible approach by minimizing abstract mathematical theories. We present a concrete numerical example with a small dataset to illustrate how clusters can be formed using the Kmeans clustering algorithm. Additionally, we provide sample codes and comparisons with the K-means model available in the scikit-learn library. Upon completing this chapter, readers will gain a comprehensive understanding of the mechanics behind K-means clustering, and its connection to the implementation and performance of the algorithm, and be well-prepared to apply it in practical use.