satyamroy15/K-Means-Clustering-Unsupervised-ML
To predict the optimum number of clusters and represent it visually, from the given ‘Iris’ dataset.
No commits in the last 6 months.
Stars
2
Forks
3
Language
Jupyter Notebook
License
—
Category
Last pushed
Sep 20, 2020
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/satyamroy15/K-Means-Clustering-Unsupervised-ML"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
scikit-learn-contrib/hdbscan
A high performance implementation of HDBSCAN clustering.
annoviko/pyclustering
pyclustering is a Python, C++ data mining library.
panagiotisanagnostou/HiPart
Hierarchical divisive clustering algorithm execution, visualization and Interactive visualization.
wq2012/SpectralCluster
Python re-implementation of the (constrained) spectral clustering algorithms used in Google's...
mqcomplab/MDANCE
MDANCE: O(N) clustering for molecular dynamics. Process 1.5M frames in 40min. 8 specialized algorithms.