Metadata-Version: 2.1
Name: qsarify
Version: 0.1
Summary: QSARify: A tool for QSAR model development
Project-URL: repository, https://github.com/stephenszwiec/qsarify
Project-URL: issues, https://github.com/stephenszwiec/qsarify/issues
Project-URL: homepage, https://stephenszwiec.github.io/qsarify/
Project-URL: documentation, https://stephenszwiec.github.io/qsarify/
Author-email: Stephen Szwiec <Stephen.Szwiec@ndsu.edu>
License-Expression: GPL-3.0-or-later
License-File: LICENSE
Keywords: QSAR,cheminformatics,machine learning
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: scipy
Description-Content-Type: text/markdown

# qsarify

qsarify is a library of tools for the analysis of QSAR/QSPR datasets and models. This library is intended to be used to produce models which relate an X set of calculated chemical descriptors to a given numeric endpoint. Many great tools will take the geometry or string data of a given chemical and compute **descriptors**, which are numeric measures of the properties of these, but you can generate some of these with another one of my scripts, [Free Descriptors](https://github.com/StephenSzwiec/free_descriptors).

# Installation
--------------




# What is included right now?
-----------------

- Data preprocessing tools: `data_tools`
- Dimensionality reduction via clustering: `clustering`
- Feature selection:
	- Single threaded: `feature_selection_single`
	- Multi-threaded: `feature_selection_multi`
- Model Export and Visualization: `model_export`
- Cross Valiidation: `cross_validation`

# Future Plans:
---------------
-
