MAGIX: Model Agnostic Globally Interpretable Explanations

MAGIX: Model Agnostic Globally Interpretable Explanations

22 June 2017

Piyush B. Gupta

Pratiksha Agarwal

Balaji Krishnamurthy

Papers citing "MAGIX: Model Agnostic Globally Interpretable Explanations"

10 / 10 papers shown

Title
Comparison of decision trees with Local Interpretable Model-Agnostic Explanations (LIME) technique and multi-linear regression for explaining support vector regression model in terms of root mean square error (RMSE) values Amit Thombre FAtt 11 1 0 10 Apr 2024
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 40 78 0 06 May 2022
Why model why? Assessing the strengths and limitations of LIME Jurgen Dieber S. Kirrane FAtt 26 97 0 30 Nov 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 22 397 0 19 Oct 2020
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks Joseph D. Janizek Pascal Sturmfels Su-In Lee FAtt 30 143 0 10 Feb 2020
Interpretability of Blackbox Machine Learning Models through Dataview Extraction and Shadow Model creation Rupam Patir Shubham Singhal C. Anantaram Vikram Goyal 16 0 0 02 Feb 2020
LoRMIkA: Local rule-based model interpretability with k-optimal associations Dilini Sewwandi Rajapaksha Christoph Bergmeir Wray L. Buntine 35 31 0 11 Aug 2019
Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization Nina Schaaf Marco F. Huber Johannes Maucher 25 36 0 10 Apr 2019
SAFE ML: Surrogate Assisted Feature Extraction for Model Learning Alicja Gosiewska A. Gacek Piotr Lubon P. Biecek 20 5 0 28 Feb 2019
Contrastive Explanations with Local Foil Trees J. V. D. Waa M. Robeer J. Diggelen Matthieu J. S. Brinkhuis Mark Antonius Neerincx FAtt 19 82 0 19 Jun 2018