Download presentation

Presentation is loading. Please wait.

Published byJenny Folley Modified over 7 years ago

1
Agglomerative Hierarchical Clustering 1. Compute a distance matrix 2. Merge the two closest clusters 3. Update the distance matrix 4. Repeat Step 2 until only one cluster remains

2
Distance Between Clusters … Min distance Distance between two closest objects Min < threshold: Single-link Clustering Max distance Distance between two farthest objects Max < threshold: Complete-link Clustering Average distance Average of all pairs of objects from the two clusters

3
… Distance Between Clusters Mean distance Increased SSE (Ward’s Method)

4
Min Distance Clustering Example... 1 2 5 3 6 4

5
... Min Distance Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

6
Max Distance Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

7
Average Distance Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

8
Ward’s Clustering Example ©Tan, Steinbach, Kumar Introduction to Data Mining 2004

9
About Hierarchical Clustering Produces a hierarchy of clusters Lack of a global objective function Merging decisions are final Expensive Often used with other clustering algorithms

Similar presentations

© 2022 SlidePlayer.com Inc.

All rights reserved.

To make this website work, we log user data and share it with processors. To use this website, you must agree to our Privacy Policy, including cookie policy.

Ads by Google