marcelrobeer / mlxtend

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Welkom! 🇳🇱

🐻 My name is Marcel Robeer, and I am currently pursuing a PhD in Explainable Artificial Intelligence (XAI) at Utrecht University!

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🤖 My thesis projects and scientific research projects have resulted in several open-source Python packages:

• Explabox: {Explore | Examine | Explain | Expose } your AI model with the explabox!
• GlobalCausalAnalysis: Explaining Model Behavior with Global Causal Analysis (give a causal overview of how aspects such as task-related features, fairness and robustness relate to black-box model behavior) [xAI 2023 paper].
• text_explainability: A generic explainability architecture for explaining text machine learning models.
• text_sensitivity: Extension of text_explainability for sensitivity testing (robustness & fairness).
• CounterfactualGAN: Generating realistic natural language counterfactuals for classifiers and regressors, without requiring explainee intervention [EMNLP 2021 paper].
• ContrastiveExplanation: Contrastive and counterfactual explanations for machine learning with Foil Trees [WHI 2018 paper].
• VisualNarrator: Turns user stories into a conceptual model containing entities and relationships [RE 2016 paper].

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💻 Check out marcelrobeer.github.io for a full overview. See you there!