AICGijon/quantificationlib
QuantificationLib is an open-source library for quantification learning.
QuantificationLib helps data scientists and machine learning engineers accurately estimate the proportion of positive or negative instances within an unlabeled dataset, even when the models used to classify individual items are imperfect. It takes an existing dataset of classified items and improves the accuracy of the overall class distribution count. This is useful for anyone needing to understand population-level trends rather than individual predictions.
No commits in the last 6 months. Available on PyPI.
Use this if you need to know 'how many' items of a certain type are in a large collection, rather than 'which specific' items are of that type.
Not ideal if your primary goal is to improve the accuracy of individual item classifications, rather than the overall class distribution.
Stars
12
Forks
1
Language
Python
License
GPL-3.0
Last pushed
Apr 06, 2024
Commits (30d)
0
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