aequitas | Bias and Fairness Audit Toolkit | Machine Learning library
kandi X-RAY | aequitas Summary
kandi X-RAY | aequitas Summary
aequitas is a Python library typically used in Artificial Intelligence, Machine Learning applications. aequitas has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install aequitas' or download it from GitHub, PyPI.
Aequitas is an open-source bias audit toolkit for data scientists, machine learning researchers, and policymakers to audit machine learning models for discrimination and bias, and to make informed and equitable decisions around developing and deploying predictive tools.
Aequitas is an open-source bias audit toolkit for data scientists, machine learning researchers, and policymakers to audit machine learning models for discrimination and bias, and to make informed and equitable decisions around developing and deploying predictive tools.
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aequitas has a low active ecosystem.
It has 531 star(s) with 94 fork(s). There are 43 watchers for this library.
There were 2 major release(s) in the last 6 months.
There are 43 open issues and 22 have been closed. On average issues are closed in 77 days. There are 5 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of aequitas is 1.0.0.dev0
Quality
aequitas has 0 bugs and 0 code smells.
Security
aequitas has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
aequitas code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
aequitas is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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aequitas releases are not available. You will need to build from source code and install.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions, examples and code snippets are available.
aequitas saves you 10910 person hours of effort in developing the same functionality from scratch.
It has 22161 lines of code, 211 functions and 98 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed aequitas and discovered the below as its top functions. This is intended to give you an instant insight into aequitas implemented functionality, and help decide if they suit your requirements.
- Creates a chart for the x_metrics chart
- Draw the legend
- Draw the plots
- Draw axis rules
- Plot a summary chart
- Draw the attribute title
- Draws the parity test case
- Draw the line titles for each metric
- Calculates therosstabs of all the models
- Prepare the x_chart
- Get the database connection
- Squarify rectangle
- Creates a chart size
- Prepare a summary chart
- Run audit on each model
- Parse command line arguments
- Plots the disparity disparity plot
- Prepares a bubble chart
- Compute the similarity between two models
- Displays the similarity between two models
- Creates a divider chart
- Generates a concatenated graphic chart
- Plots a fairness group
- Plot a metric for multiple models
- Creates a heatmap chart
- Audit a single file
Get all kandi verified functions for this library.
aequitas Key Features
No Key Features are available at this moment for aequitas.
aequitas Examples and Code Snippets
No Code Snippets are available at this moment for aequitas.
Community Discussions
Trending Discussions on aequitas
QUESTION
python json remove() element issue for a while condition
Asked 2017-Aug-10 at 19:17
I have a json file in the following format. What I need to do is to get rid of the whole dictionary of elements where the "URI" does not contain "http"
...ANSWER
Answered 2017-Aug-08 at 16:06Don't modify a list while iterating over it. Doing so can produce unexpected behavior. Instead, you can use a list comprehension to filter elements from your JSON list:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install aequitas
Aequitas is compatible with: Python 3.6+.
Support
You can find the toolkit documentation here. For usage examples of the python library, see our demo notebook from the KDD 2020 hands-on tutorial. Alternatively, have a look to COMPAS notebook using Aequitas on the ProPublica COMPAS Recidivism Risk Assessment dataset.
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