k_means_python
Computation application for the k-means algorithm is an unsupervised clustering technique that organizes data into clusters based on similarity. It iteratively assigns data points to centroids and recalculates centroids based on the average of assigned points until the variance between points and centroids is minimized.
Science Score: 13.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
-
○DOI references
-
○Academic links in README
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (0.9%) to scientific vocabulary
Repository
Computation application for the k-means algorithm is an unsupervised clustering technique that organizes data into clusters based on similarity. It iteratively assigns data points to centroids and recalculates centroids based on the average of assigned points until the variance between points and centroids is minimized.
Basic Info
- Host: GitHub
- Owner: edendenis
- License: other
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://www.edftechnology.com
- Size: 106 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 1
Metadata Files
Owner
- Login: edendenis
- Kind: user
- Repositories: 1
- Profile: https://github.com/edendenis
GitHub Events
Total
- Watch event: 1
- Push event: 1
Last Year
- Watch event: 1
- Push event: 1