  QuaPy is an open-source framework for performing quantification (a.k.a.
supervised prevalence estimation), written in Python. Quantification is the
task of training quantifiers via supervised learning, where a quantifier is a
predictor that estimates the relative frequencies (a.k.a. prevalence values) of
the classes of interest in a sample of unlabelled data. While quantification
can be trivially performed by applying a standard classifier to each unlabelled
data item and counting how many data items have been assigned to each class, it
has been shown that this "classify and count" method is outperformed by methods
specifically designed for quantification. QuaPy provides implementations of a
number of baseline methods and advanced quantification methods, of routines for
quantification-oriented model selection, of several broadly accepted evaluation
measures, and of robust evaluation protocols routinely used in the field. QuaPy
also makes available datasets commonly used for testing quantifiers, and offers
visualization tools for facilitating the analysis and interpretation of the
results. The software is open-source and publicly available under a BSD-3
licence via https://github.com/HLT-ISTI/QuaPy, and can be installed via pip
(https://pypi.org/project/QuaPy/)
