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dalex

swMATH ID: 36558
Software Authors: Baniecki, Hubert; Kretowicz, Wojciech; Piatyszek, Piotr; Wisniewski, Jakub; Biecek, Przemyslaw
Description: dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python. The increasing amount of available data, computing power, and the constant pursuit for higher performance results in the growing complexity of predictive models. Their black-box nature leads to opaqueness debt phenomenon inflicting increased risks of discrimination, lack of reproducibility, and deflated performance due to data drift. To manage these risks, good MLOps practices ask for better validation of model performance and fairness, higher explainability, and continuous monitoring. The necessity of deeper model transparency appears not only from scientific and social domains, but also emerging laws and regulations on artificial intelligence. To facilitate the development of responsible machine learning models, we showcase dalex, a Python package which implements the model-agnostic interface for interactive model exploration. It adopts the design crafted through the development of various tools for responsible machine learning; thus, it aims at the unification of the existing solutions. This library’s source code and documentation are available under open license at this https URL.
Homepage: https://dalex.drwhy.ai/python/
Source Code:  https://github.com/ModelOriented/DALEX/tree/master/python/dalex
Dependencies: Python
Keywords: Machine Learning; arXiv_cs.LG; arXiv_cs.HC; arXiv_cs.SE; arXiv_stat.ML; dalex; Python; explainability; fairness; interactivity; responsible ml
Related Software: DALEX; shap; AI Explainability 360; Python; InterpretML; Alibi Explain; Fairlearn; H2O; Alibi; XGBoost; NumPy; Scikit; LightGBM; modelStudio; TensorFlow; PDPbox; BRITS; Espresso; NIMEFI; auto-sklearn
Cited in: 2 Documents

Standard Articles

1 Publication describing the Software Year
dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python arXiv
Hubert Baniecki, Wojciech Kretowicz, Piotr Piatyszek, Jakub Wisniewski, Przemyslaw Biecek
2020

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