Metadata-Version: 2.1
Name: pyampute
Version: 0.0.3
Summary: Transformer for generating multivariate missingness in complete datasets
Home-page: UNKNOWN
Author: Rianne Schouten,Davina Zamanzadeh,Prabhant Singh
Author-email: r.m.schouten@tue.nl,davzaman@gmail.com,p.singh@tue.nl
License: BSD
Project-URL: Documentation, https://rianneschouten.github.io/pyampute/build/html/index.html
Project-URL: Source Code, https://github.com/RianneSchouten/pyampute
Platform: UNKNOWN
License-File: LICENSE.md
Requires-Dist: pandas
Requires-Dist: numpy (>=1.19.0)
Requires-Dist: scipy
Requires-Dist: matplotlib (>=3.4.0)
Requires-Dist: scikit-learn
Provides-Extra: docs
Requires-Dist: sphinx ; extra == 'docs'
Requires-Dist: pydata-sphinx-theme ; extra == 'docs'
Requires-Dist: sphinx-autodoc-typehints ; extra == 'docs'
Requires-Dist: sphinx-gallery ; extra == 'docs'

Amputation is the opposite of imputation; it is the creation of a missing data mask for complete datasets. Amputation is useful for evaluating the effect of missing values on the outcome of a statistical or machine learning model. ``pyampute`` is the first open-source Python library for data amputation. Our package is compatible with the scikit-learn-style fit and transform paradigm, which allows for seamless integration of amputation in a larger, more complex data processing pipeline.

