What are the types of clustering?

What are the different types of clustering methods?

There are several types of clustering methods, including hierarchical, k-means, and DBSCAN. Would you like to know more about any specific type?

Can you explain k-means clustering?

K-means clustering is a method that partitions data into k distinct clusters based on feature similarity. It works by initializing k centroids and iteratively assigning data points to the nearest centroid, then updating the centroids based on the assigned points.

What about hierarchical clustering?

Hierarchical clustering builds a tree of clusters by either a divisive method (starting with one cluster and splitting) or an agglomerative method (starting with individual points and merging). It provides a visual representation through a dendrogram.

What is DBSCAN?

DBSCAN stands for Density-Based Spatial Clustering of Applications with Noise. It groups together points that are closely packed together while marking points in low-density regions as outliers.