Alibi Explain

Open source Python library aimed at machine learning model inspection and interpretation.

Alibi Explain

Open source Python library aimed at machine learning model inspection and interpretation.

Ensure stability of model performance.

When your data changes so can your models predictions. Ensure accuracy by monitoring alteration.

Strengthen intuition for feature selection.

Gain insights into how features influence model performance.

Derive a set of features and attributes for consistent prediction.

Return the score that indicates the presence of features & instances that trick the model outcome.

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Highlights

Feature Alteration

Feature Alteration

See how prediction changes and ensure stability of model performance against changing data.

Feature Impact

Feature Impact

Alibi indicates how features influence model performance, strengthening intuition for feature selection.

Necessary Features

Necessary Features

Focus on critical data attributes and features by deriving a set of features and attributes for consistent prediction.

Feature Attribution

Feature Attribution

Build confidence in integrity of model performance when Alibi illustrates prediction dynamics when features change

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You’ll find Alibi Explain on GitHub 

See it for yourself

Serve, monitor, explain, and manage your models today.

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