These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Microsoft InterpretML
Why InterpretML?
Model Interpretability
Model interpretability helps developers, data scientists and business stakeholders in the organization gain a comprehensive understanding of their machine learning models. It can also be used to debug models, explain predictions and enable auditing to meet compliance with regulatory requirements.
Ease of use
Access state-of-the-art interpretability techniques through an open unified API set and rich visualizations.
Flexible and customizable
Understand models using a wide range of explainers and techniques using interactive visuals. Choose your algorithm and easily experiment with combinations of algorithms.
Comprehensive capabilities
Explore model attributes such as performance, global and local features and compare multiple models simultaneously. Run what-if analysis as you manipulate data and view the impact on the model.
Types of Models Supported
About the tool
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Use Cases
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