https://github.com/msikorski93/seed-clustering
Performing basic clustering on a seeds dataset.
https://github.com/msikorski93/seed-clustering
agglomerative clustering dbscan gaussian-mixture-model gmm mini-batch-kmeans scikit-learn seeds
Last synced: 4 months ago
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Performing basic clustering on a seeds dataset.
- Host: GitHub
- URL: https://github.com/msikorski93/seed-clustering
- Owner: msikorski93
- Created: 2023-10-25T19:36:08.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-10-25T20:05:56.000Z (over 1 year ago)
- Last Synced: 2025-01-09T07:51:10.687Z (6 months ago)
- Topics: agglomerative, clustering, dbscan, gaussian-mixture-model, gmm, mini-batch-kmeans, scikit-learn, seeds
- Language: Jupyter Notebook
- Homepage:
- Size: 929 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Seed-Clustering





The subject of this repository was to perform basic cluster analysis on a seed dataset. The dataset contains geometrical properties of kernels belonging to three different varieties of wheat. We performed four different clustering approaches and obtained these results:
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The agglomerative clustering turned out to be the best choice. DBSCAN had the lowest performance, however it looks more suitable for detecting outliers in datasets.