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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: about 2 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 (almost 3 years ago)
- Last Synced: 2024-04-11T01:50:39.566Z (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
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Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- 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))