Metadata-Version: 2.1
Name: virny
Version: 0.3.0
Summary: Python library for auditing model stability and fairness
Home-page: https://github.com/DataResponsibly/Virny
Author: Denys Herasymuk
Author-email: denis.gerasymuk799@gmail.com
License: BSD-3
Description: # Virny Software Library
        
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        ## 📜 Description
        
        **Virny** is a Python library for auditing model stability and fairness. The Virny library was
        developed based on three fundamental principles: 
        
        1) easy extensibility of model analysis capabilities;
        
        2) compatibility to user-defined/custom datasets and model types;
        
        3) simple composition of parity metrics based on context of use.
        
        Virny decouples model auditing into several stages, including: **subgroup metrics computation**, **group metrics composition**,
        and **metrics visualization and reporting**. This gives data scientists and practitioners more control and flexibility 
        to use the library for model development and monitoring post-deployment.
        
        For quickstart, look at our [Use Case Examples](https://dataresponsibly.github.io/Virny/examples/Multiple_Models_Interface_Use_Case/).
        
        
        ## 🛠 Installation
        
        Virny supports **Python 3.8 (recommended), 3.9** and can be installed with `pip`:
        
        ```bash
        pip install virny
        ```
        
        
        ## 📒 Documentation
        
        * [Introduction](https://dataresponsibly.github.io/Virny/)
        * [API Reference](https://dataresponsibly.github.io/Virny/api/overview/)
        * [Use Case Examples](https://dataresponsibly.github.io/Virny/examples/Multiple_Models_Interface_Use_Case/)
        
        
        ## 💡 Features
        
        * Entire pipeline for auditing model stability and fairness
        * Metrics reports and visualizations
        * Ability to analyze intersections of sensitive attributes
        * Convenient metric computation interfaces: an interface for multiple models, an interface for multiple test sets, and an interface for saving results into a user-defined database
        * An `error_analysis` computation mode to analyze model stability and confidence for correct and incorrect prodictions splitted by groups
        * Data loaders with subsampling for fairness datasets
        * User-friendly parameters input via config yaml files
        * Check out [our documentation](https://dataresponsibly.github.io/Virny/) for a comprehensive overview
        
        
        ## 📖 Library Terminology
        
        This section briefly explains the main terminology used in our library.
        
        * A **sensitive attribute** is an attribute that partitions the population into groups with unequal benefits received.
        * A **protected group** (or simply _group_) is created by partitioning the population by one or many sensitive attributes.
        * A **privileged value** of a sensitive attribute is a value that gives more benefit to a protected group, which includes it, than to protected groups, which do not include it.
        * A **subgroup** is created by splitting a protected group by privileges and disprivileged values.
        * A **group metric** is a metric that shows the relation between privileged and disprivileged subgroups created based on one or many sensitive attributes.
        
        
        ## 🤗 Affiliations
        
        ![NYU-UCU-Logos](https://user-images.githubusercontent.com/42843889/216840888-071bf184-f0e3-4a3e-94dc-c0d1c7784143.png)
        
        
        ## 📝 License
        
        **Virny** is free and open-source software licensed under the [3-clause BSD license](https://github.com/DataResponsibly/Virny/blob/main/LICENSE).
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Provides-Extra: dev
Provides-Extra: docs
