What are the benefits of hierarchical clustering?

What are the benefits of hierarchical clustering?

Hierarchical clustering offers several benefits, including the ability to create a tree-like structure of data, which helps in visualizing relationships. It doesn't require a predefined number of clusters, making it flexible for various datasets.

Can you explain how it differs from k-means clustering?

Certainly! Unlike k-means, which requires you to specify the number of clusters beforehand, hierarchical clustering builds a hierarchy of clusters without needing that information. This allows for more exploratory data analysis.

What types of data are best suited for hierarchical clustering?

Hierarchical clustering works well with small to medium-sized datasets and is particularly effective for categorical data or when the relationships between data points are complex.

Are there any limitations I should be aware of?

Yes, some limitations include its computational intensity for large datasets and sensitivity to noise and outliers, which can affect the clustering results.