Hierarchical clustering is a cool way to see how different pieces of data are connected. It creates a picture called a dendrogram, which looks like a tree. This picture shows how data points are grouped together.
Here are some key points about hierarchical clustering:
Flexibility: You can adjust how detailed you want the grouping to be. By slicing the dendrogram at different heights, you get different levels of detail.
Illustrative Examples: For example, if you're looking at what customers like, you can see how similar different product types are.
This process helps you understand the natural groups in your data and also spot anything that doesn't seem to fit in, called outliers. By looking at these connections, you can make better choices based on how your data is organized.
Hierarchical clustering is a cool way to see how different pieces of data are connected. It creates a picture called a dendrogram, which looks like a tree. This picture shows how data points are grouped together.
Here are some key points about hierarchical clustering:
Flexibility: You can adjust how detailed you want the grouping to be. By slicing the dendrogram at different heights, you get different levels of detail.
Illustrative Examples: For example, if you're looking at what customers like, you can see how similar different product types are.
This process helps you understand the natural groups in your data and also spot anything that doesn't seem to fit in, called outliers. By looking at these connections, you can make better choices based on how your data is organized.