dayyass/graph-based-clustering
Graph-Based Clustering using connected components and spanning trees.
This tool helps data analysts and researchers group similar data points together into meaningful clusters. You provide numerical data, and it identifies natural groupings within it, assigning a cluster label to each data point. It's ideal for anyone needing to segment data based on inherent similarities, like customer segmentation or document categorization.
No commits in the last 6 months. Available on PyPI.
Use this if you need to find inherent groupings within a fixed dataset and want to specify either a distance threshold for grouping or the exact number of clusters you expect.
Not ideal if you need to classify new, unseen data points into existing clusters after the initial grouping, as it is designed for transductive clustering on the original dataset.
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Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 01, 2021
Commits (30d)
0
Dependencies
3
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