DBSCAN Clustering Algorithm Solved Numerical Example in Machine Learning Data Mining Mahesh Huddar

The DBSCAN clustering algorithm is applied to 12 data points, forming clusters based on a minimum of four points within a distance of 1.9. Distances between points are calculated, nearest points identified, and core, border, and noise points determined, resulting in three clusters while noting P9 as an outlier.