Error Analysis
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About
Error Analysis is a Responsible AI toolkit designed to help evaluate machine learning model errors beyond aggregate accuracy. It allows users to identify cohorts with high error rates compared to benchmarks, visualize error rate distributions, and diagnose root causes through various methods such as data exploration and what-if analysis. The tool features an interactive dashboard for customizable visuals, supports built-in interpretability features, and encourages community contributions for continued development.
Platform
Task
Features
• identify cohorts with high error rates
• diagnose root causes of errors
• what-if analysis to observe prediction changes
• global and local explanations of model predictions
• data exploration and feature distributions comparison
• different methods for error identification
• interactive dashboard for error analysis
• explore predictions with interpretability features
• visualize error distributions
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