The error analysis sdk enables users to get a deeper understanding of machine learning model errors. When evaluating a machine learning model, aggregate accuracy is not sufficient and single-score evaluation may hide important conditions of inaccuracies. Use Error Analysis to identify cohorts with higher error rates and diagnose the root causes behind these errors.
Highlights of the package include:
Please see the main documentation website: https://erroranalysis.ai/
Auto-generated sphinx API documentation can be found here: https://erroranalysis.ai/raiwidgets.html
The open source code can be found here: https://github.com/microsoft/responsible-ai-widgets
FAQs
Core error analysis APIs
We found that erroranalysis demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
PyPI confirms no security flaws were exploited in the Ultralytics supply chain attack and highlights improvements for safer package publishing.
Security News
Research
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
