uber/manifold

A model-agnostic visual debugging tool for machine learning

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/ 100
Emerging

When you're trying to understand why your machine learning models are making mistakes, Manifold helps you visually pinpoint exactly which data points are causing issues and why. You provide your model's predictions, the actual correct answers, and the input data features. Manifold then shows you interactive visualizations that highlight underperforming data segments and the specific input features contributing to those errors. This tool is for data scientists, machine learning engineers, and researchers who need to debug and improve their ML models beyond just looking at overall performance scores.

1,672 stars. No commits in the last 6 months.

Use this if you need to visually analyze why your machine learning model performs poorly on certain data subsets and identify the input features that correlate with those errors.

Not ideal if you're looking for an automated model training solution or a tool to deploy models into production.

machine-learning-debugging model-explainability data-science-workflow predictive-modeling performance-analysis
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 17 / 25

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Stars

1,672

Forks

116

Language

JavaScript

License

Apache-2.0

Last pushed

Feb 05, 2025

Commits (30d)

0

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