LuisScoccola/persistable
density-based clustering for exploratory data analysis based on multi-parameter persistence
This tool helps data analysts and researchers understand the underlying structure in their datasets by identifying natural groupings or clusters. You input raw numerical data points, and it helps you visually explore how clusters form across different scales and densities, leading to a final set of labels assigning each data point to a cluster. It's designed for anyone needing to find hidden patterns in complex datasets.
No commits in the last 6 months.
Use this if you need an interactive way to explore and determine the most meaningful clusters within your data without making strong initial assumptions.
Not ideal if you require a simple, fully automated clustering solution without any visual exploration or parameter tuning.
Stars
42
Forks
2
Language
Python
License
BSD-3-Clause
Category
Last pushed
Jul 20, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/LuisScoccola/persistable"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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