hello-chp 0.0.24

A Python library for optimal data imputation.

Hong-Lan Botterman, Julien Roussel, Thomas Morzadec, Rima Hajou, Firas Dakhli, Anh Khoa Ngo Ho, Charles-Henri Prat

Author-email: [e-mail], [e-mail], [e-mail], [e-mail], [e-mail], [e-mail], [e-mail]

License: new BSD Project-URL: Bug Tracker, https://github.com/Quantmetry/qolmat Project-URL: Documentation, https://qolmat.readthedocs.io/en/latest/ Project-URL: Source Code, https://github.com/Quantmetry/qolmat Classifier: Intended Audience :: Science/Research Classifier: Intended Audience :: Developers Classifier: License :: OSI Approved Classifier: Topic :: Software Development Classifier: Topic :: Scientific/Engineering Classifier: Operating System :: Microsoft :: Windows Classifier: Operating System :: POSIX Classifier: Operating System :: Unix Classifier: Operating System :: MacOS Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3.10 Requires-Python: >=3.8 Description-Content-Type: text/x-rst License-File: LICENSE License-File: AUTHORS.rst Requires-Dist: dcor>=0.6 Requires-Dist: hyperopt Requires-Dist: numpy>=1.19 Requires-Dist: packaging Requires-Dist: pandas>=1.3 Requires-Dist: scikit-learn Requires-Dist: scipy Requires-Dist: statsmodels>=0.14 Provides-Extra: tests Requires-Dist: flake8; extra == “tests” Requires-Dist: mypy; extra == “tests” Requires-Dist: pandas; extra == “tests” Requires-Dist: pytest; extra == “tests” Requires-Dist: pytest-cov; extra == “tests” Requires-Dist: typed-ast; extra == “tests” Provides-Extra: docs Requires-Dist: numpydoc; extra == “docs” Requires-Dist: sphinx; extra == “docs” Requires-Dist: sphinx-gallery; extra == “docs” Requires-Dist: sphinx_rtd_theme; extra == “docs” Requires-Dist: typing_extensions; extra == “docs” Provides-Extra: pytorch Requires-Dist: torch==2.0.1; extra == “pytorch”

Qolmat - The Tool for Data Imputation

Qolmat provides a convenient way to estimate optimal data imputation techniques by leveraging scikit-learn-compatible algorithms. Users can compare various methods based on different evaluation metrics.

🔗 Requirements

Python 3.8+

🛠 Installation

Qolmat can be installed in different ways:

$ pip install qolmat  # installation via `pip`
$ pip install qolmat[tensorflow] # if you need tensorflow
$ pip install git+https://github.com/Quantmetry/qolmat  # or directly from the github repository