Surrogate Locally-Interpretable Models with Supervised Machine Learning
Algorithms

Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms

28 July 2020

Jie Chen

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Papers citing "Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms"

9 / 9 papers shown

Title
Effector: A Python package for regional explanations Vasilis Gkolemis Christos Diou Eirini Ntoutsi Theodore Dalamagas B. Bischl J. Herbinger Giuseppe Casalicchio CML 72 1 0 03 Apr 2024
Leveraging Model-based Trees as Interpretable Surrogate Models for Model Distillation J. Herbinger Susanne Dandl F. K. Ewald Sofia Loibl Giuseppe Casalicchio TPM 46 3 0 04 Oct 2023
Monotone Tree-Based GAMI Models by Adapting XGBoost Linwei Hu Soroush Aramideh Jie Chen V. Nair 57 1 0 05 Sep 2023
Interpretable Machine Learning based on Functional ANOVA Framework: Algorithms and Comparisons Linwei Hu V. Nair Agus Sudjianto Aijun Zhang Jie Chen 68 8 0 25 May 2023
Using Model-Based Trees with Boosting to Fit Low-Order Functional ANOVA Models Linwei Hu Jie Chen V. Nair 77 3 0 14 Jul 2022
Shapley Computations Using Surrogate Model-Based Trees Zhipu Zhou Jie Chen Linwei Hu 44 0 0 11 Jul 2022
REPID: Regional Effect Plots with implicit Interaction Detection J. Herbinger Bernd Bischl Giuseppe Casalicchio FAtt 58 15 0 15 Feb 2022
The Self-Simplifying Machine: Exploiting the Structure of Piecewise Linear Neural Networks to Create Interpretable Models William Knauth 19 1 0 02 Dec 2020
Supervised Machine Learning Techniques: An Overview with Applications to Banking Linwei Hu Jie Chen J. Vaughan Hanyu Yang Kelly Wang Agus Sudjianto V. Nair 44 23 0 28 Jul 2020