https://github.com/navdeep-G/h2o3-pam

Implementation of Partitioning Around Medoids (PAM) in H2O-3
https://github.com/navdeep-G/h2o3-pam

big-data clustering clustering-algorithm data-science distributed h2o h2o-3 java machine-learning medoids multithreading pam unsupervised-learning

Last synced: 3 months ago
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Implementation of Partitioning Around Medoids (PAM) in H2O-3

• Host: GitHub
• URL: https://github.com/navdeep-G/h2o3-pam
• Owner: navdeep-G
• License: apache-2.0
• Created: 2018-03-19T22:25:18.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-10-04T23:18:46.000Z (over 2 years ago)
• Last Synced: 2024-01-22T18:36:03.886Z (5 months ago)
• Topics: big-data, clustering, clustering-algorithm, data-science, distributed, h2o, h2o-3, java, machine-learning, medoids, multithreading, pam, unsupervised-learning
• Language: Java
• Homepage:
• Size: 101 KB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-h2o - h2o3-pam - 3 (Software)

README

        
# Partitioning Around Medoids (PAM)

## Implementation of Partitioning Around Medoids (PAM) in [H2O-3](https://github.com/h2oai/h2o-3)

### Pros:

- Deterministic in nature

- Outperforms k-means for some applications

### Cons:

- Inherently `O(n^2)` time and possibly space depending on implementation 

### References: 

* pp.102-104 of `Finding Groups in Data by Kaufman and Rousseeuw`.

* [https://en.wikipedia.org/wiki/K-medoids](https://en.wikipedia.org/wiki/K-medoids)

* [https://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/Partitioning_Around_Medoids_(PAM)](https://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/Partitioning_Around_Medoids_(PAM))