Step 1: Understand what clustering means. Clustering is a way to group similar data points together.
Step 2: Learn about different types of clustering algorithms. Some algorithms group data based on distance, while others use density.
Step 3: Identify the density-based clustering algorithm. The algorithm that focuses on the density of data points is called DBSCAN.
Step 4: Know what DBSCAN stands for. It stands for Density-Based Spatial Clustering of Applications with Noise.
Step 5: Understand how DBSCAN works. It finds clusters by looking for areas where data points are close together (high density) and separates them from areas with fewer points (low density).
