lanl/pyDNMFk
Python Distributed Non Negative Matrix Factorization with custom clustering
This tool helps scientists and researchers analyze very large datasets to find hidden patterns and features, even when the exact number of features isn't known beforehand. You input your raw data, and it outputs the underlying components and their relationships, along with an estimated optimal number of features. It's designed for those working with massive datasets where traditional methods might be too slow.
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Use this if you need to discover underlying factors or groupings in large, complex datasets and want an automated way to determine the optimal number of those factors.
Not ideal if you are working with small datasets or if you already know the exact number of features you want to extract.
Stars
24
Forks
6
Language
Python
License
BSD-3-Clause
Category
Last pushed
Aug 22, 2023
Commits (30d)
0
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