luizfernandolj/mlquantify
A Python Quantification Library
When you have a large dataset of classified items and need to understand the proportion of each class within that data, this tool helps you accurately estimate those class distributions. It takes your labeled training data and new, unlabelled data, then outputs the estimated percentage of each class in the new data. This is useful for data scientists, machine learning practitioners, or anyone working with large classification datasets who needs to understand population shifts without labeling every item.
Use this if you need to determine the prevalence of different categories within an unlabeled dataset, especially when manually labeling everything is too time-consuming or costly.
Not ideal if your primary goal is to classify individual data points or if you only need to know the overall count of items, not their proportional distribution.
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9
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1
Language
Python
License
BSD-3-Clause
Category
Last pushed
Feb 25, 2026
Commits (30d)
0
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