https://github.com/theogrammer/dsc411-clustering
https://github.com/theogrammer/dsc411-clustering
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/theogrammer/dsc411-clustering
- Owner: theogrammer
- Created: 2023-03-15T19:49:06.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-03-20T03:50:14.000Z (about 2 years ago)
- Last Synced: 2025-01-30T04:25:33.595Z (3 months ago)
- Language: Python
- Size: 33.2 KB
- Stars: 0
- Watchers: 2
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Bisecting K-means algorithm
Implementation of the Bisecting K-means clustering algorithm in Python with some additional methods for initializing centroids, calculating SSE, and getting labels for data points to clusters.
It accepts a CSV file that has a varied set of features. You may use the Euclidean algorithm as your proximity measure or any other proximity measure of your choice. (You may choose a different distance measure for this assignment) You can use this CSV
The program outputs a printout of the centroids and the SSE. We also return the original dataset with cluster assignments. Additionally, we created a 3D visualization using the first 3 features of the dataset.
# Visualization
## Authors
- [@brent-caldwell-3](https://github.com/brent-caldwell-3)
- [@teddygizachew](https://github.com/teddygizachew)
- [@oliviaryan]()