Metadata-Version: 2.1
Name: mvlearn
Version: 0.2.1
Summary: A set of python modules for multiview learning
Home-page: https://github.com/NeuroDataDesign/mvlearn
Author: ('Richard Guo', 'Ronan Perry', 'Gavin Mischler', 'Theo Lee', 'Alexander Chang', 'Arman Koul', 'Cameron Franz')
Author-email: rflperry@gmail.com
License: Apache License 2.0
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Requires-Dist: graspy (>=0.1.1)
Requires-Dist: matplotlib (>=3.0.0)
Requires-Dist: numpy (>=1.17.0)
Requires-Dist: pandas (>=0.25.0)
Requires-Dist: scikit-learn (>=0.19.1)
Requires-Dist: scipy (>=1.1.0)
Requires-Dist: seaborn (>=0.9.0)
Requires-Dist: joblib (>=0.11)
Provides-Extra: torch
Requires-Dist: torch (>=1.1.0) ; extra == 'torch'
Requires-Dist: tqdm ; extra == 'torch'

# mvlearn

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`mvlearn` is an open-source Python software package for multi-view learning tools.

- [**Installation Guide**](https://mvlearn.neurodata.io/install.html)
- [**Documentation**](https://mvlearn.neurodata.io/index.html)
- [**Tutorials**](https://mvlearn.neurodata.io/tutorials.html)
- [**Source Code**](https://github.com/neurodata/mvlearn/tree/master/mvlearn)
- [**Issues**](https://github.com/neurodata/mvlearn/issues)
- [**Contribution Guide**](https://mvlearn.neurodata.io/contributing.html)
- [**Changelog**](https://mvlearn.neurodata.io/changelog.html)

In many data sets, there are multiple measurement modalities of the same subject, i.e. multiple *X* matrices (views) for the same class label vector *y*. For example, one may have both an MRI and CT scan of a diseased patient. Traditional methods for inference and analysis are often poorly suited to account for multiple views of the same subject as they cannot account for complementing views that hold different statistical properties. `mvlearn` provides a well-documented and tested collection of utilities and algorithms designed for the processing and analysis of multi-view data sets.


