InterpretML: See how AI makes decisions, simply
Meet a tool that helps you peek inside AI so it's less of a mystery.
InterpretML is open-source and gives people a way to compare different methods for explaining how predictions are made.
Some approaches are built so you can read them directly, like simple, clear models called glassbox models, and other tools help explain already-trained systems, which we call blackbox explainability.
The package also brings a new kind of model that aims to be both easy to read and very accurate, called the Explainable Boosting Machine.
You can test different methods side-by-side, and see results with an inbuilt visualization platform that makes patterns pop out.
It's friendly for people who just want to understand their AI, and also for researchers who try lots of ideas.
Try it and you might find surprising reasons behind a decision, and feel more confident using AI in real life.
It’s simple to start with, even if you only know a bit about data.
Read article comprehensive review in Paperium.net:
InterpretML: A Unified Framework for Machine Learning Interpretability
🤖 This analysis and review was primarily generated and structured by an AI . The content is provided for informational and quick-review purposes.
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