What are the differences between agglomerative and divisive clustering?

What are the differences between agglomerative and divisive clustering?

Agglomerative clustering is a bottom-up approach where each data point starts as its own cluster and merges them, while divisive clustering is a top-down approach that starts with one cluster and splits it into smaller ones.

Can you give me an example of each method?

Sure! In agglomerative clustering, you might start with individual points like cities and merge them based on distance. In divisive clustering, you could start with all customers in one group and split them based on purchasing behavior.

Which method is more commonly used?

Agglomerative clustering is more commonly used due to its simplicity and effectiveness in many scenarios, especially with smaller datasets.

Are there any specific use cases for divisive clustering?

Yes, divisive clustering can be useful in scenarios where you have a large dataset and want to identify distinct subgroups, like in market segmentation.