Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance

1 May 2019

Papers citing "Unrestricted Permutation forces Extrapolation: Variable Importance Requires at least One More Model, or There Is No Free Variable Importance"

50 / 59 papers shown

Title
Suboptimal Shapley Value Explanations Xiaolei Lu FAtt 63 0 0 17 Feb 2025
How Your Location Relates to Health: Variable Importance and Interpretable Machine Learning for Environmental and Sociodemographic Data Ishaan Maitra Raymond Lin Eric Chen J. Donnelly Sanja Šćepanović Cynthia Rudin 26 1 0 03 Jan 2025
Targeted Learning for Variable Importance Xiaohan Wang Yunzhe Zhou Giles Hooker 28 0 0 04 Nov 2024
Disentangling Interactions and Dependencies in Feature Attribution Gunnar König Eric Günther Ulrike von Luxburg FAtt 53 1 0 31 Oct 2024
Global Censored Quantile Random Forest Siyu Zhou Limin Peng 16 0 0 16 Oct 2024
Multi forests: Variable importance for multi-class outcomes Roman Hornung Alexander Hapfelmeier 26 1 0 13 Sep 2024
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression Ricardo Baptista Eliza O'Reilly Yangxinyu Xie 27 2 0 13 Jul 2024
Position: A Call to Action for a Human-Centered AutoML Paradigm Marius Lindauer Florian Karl A. Klier Julia Moosbauer Alexander Tornede Andreas Mueller Frank Hutter Matthias Feurer Bernd Bischl 36 6 0 05 Jun 2024
Variable importance measure for spatial machine learning models with application to air pollution exposure prediction Si Cheng M. Blanco L. Sheppard Ali Shojaie Adam Szpiro 24 0 0 04 Jun 2024
Regression Trees Know Calculus Nathan Wycoff 24 0 0 22 May 2024
Why do explanations fail? A typology and discussion on failures in XAI Clara Bove Thibault Laugel Marie-Jeanne Lesot C. Tijus Marcin Detyniecki 26 2 0 22 May 2024
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots Xi Xin Giles Hooker Fei Huang AAML 38 6 0 29 Apr 2024
SIDEs: Separating Idealization from Deceptive Explanations in xAI Emily Sullivan 44 2 0 25 Apr 2024
T-Explainer: A Model-Agnostic Explainability Framework Based on Gradients Evandro S. Ortigossa Fábio F. Dias Brian Barr Claudio T. Silva L. G. Nonato FAtt 47 2 0 25 Apr 2024
A Guide to Feature Importance Methods for Scientific Inference F. K. Ewald Ludwig Bothmann Marvin N. Wright B. Bischl Giuseppe Casalicchio Gunnar Konig 28 10 0 19 Apr 2024
Beyond development: Challenges in deploying machine learning models for structural engineering applications M. Z. Esteghamati Brennan Bean Henry V. Burton M. Z. Naser AI4CE 23 1 0 18 Apr 2024
Interpretable Machine Learning for Survival Analysis Sophie Hanna Langbein Mateusz Krzyzinski Mikolaj Spytek Hubert Baniecki P. Biecek Marvin N. Wright 43 2 0 15 Mar 2024
Challenges in Variable Importance Ranking Under Correlation Annie Liang T. Jemielita Andy Liaw V. Svetnik Lingkang Huang Richard Baumgartner Jason M. Klusowski 25 1 0 05 Feb 2024
Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks Stefan Blücher Johanna Vielhaben Nils Strodthoff AAML 61 20 0 12 Jan 2024
Factor Importance Ranking and Selection using Total Indices Chaofan Huang V. R. Joseph 13 1 0 01 Jan 2024
Variable Importance in High-Dimensional Settings Requires Grouping Ahmad Chamma Bertrand Thirion D. Engemann 32 3 0 18 Dec 2023
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 24 0 0 20 Nov 2023
The Disagreement Problem in Faithfulness Metrics Brian Barr Noah Fatsi Leif Hancox-Li Peter Richter Daniel Proano Caleb Mok 36 4 0 13 Nov 2023
Using Slisemap to interpret physical data Lauri Seppäläinen Anton Björklund V. Besel Kai Puolamäki 19 1 0 24 Oct 2023
Model-agnostic variable importance for predictive uncertainty: an entropy-based approach Danny Wood Theodore Papamarkou Matt Benatan Richard Allmendinger FAtt UD 30 3 0 19 Oct 2023
MMD-based Variable Importance for Distributional Random Forest Clément Bénard Jeffrey Näf Julie Josse 34 0 0 18 Oct 2023
Stabilizing Estimates of Shapley Values with Control Variates Jeremy Goldwasser Giles Hooker FAtt 24 4 0 11 Oct 2023
The Blame Problem in Evaluating Local Explanations, and How to Tackle it Amir Hossein Akhavan Rahnama ELM FAtt 28 4 0 05 Oct 2023
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance J. Donnelly Srikar Katta Cynthia Rudin E. Browne FAtt 14 15 0 24 Sep 2023
Statistically Valid Variable Importance Assessment through Conditional Permutations Ahmad Chamma D. Engemann Bertrand Thirion 11 10 0 14 Sep 2023
survex: an R package for explaining machine learning survival models Mikolaj Spytek Mateusz Krzyzinski Sophie Hanna Langbein Hubert Baniecki Marvin N. Wright P. Biecek 31 16 0 30 Aug 2023
Variable importance for causal forests: breaking down the heterogeneity of treatment effects Clément Bénard Julie Josse CML 31 4 0 07 Aug 2023
Shapley Sets: Feature Attribution via Recursive Function Decomposition Torty Sivill Peter A. Flach FAtt TDI 11 1 0 04 Jul 2023
Can predictive models be used for causal inference? Maximilian Pichler F. Hartig OOD CML 24 3 0 18 Jun 2023
Explaining Predictive Uncertainty with Information Theoretic Shapley Values David S. Watson Joshua O'Hara Niek Tax Richard Mudd Ido Guy TDI FAtt 26 21 0 09 Jun 2023
Dear XAI Community, We Need to Talk! Fundamental Misconceptions in Current XAI Research Timo Freiesleben Gunnar Konig 23 19 0 07 Jun 2023
Asymmetric feature interaction for interpreting model predictions Xiaolei Lu Jianghong Ma Haode Zhang FAtt 11 4 0 12 May 2023
Opening the random forest black box by the analysis of the mutual impact of features Luca Voges Lukas C. Jarren Stephan Seifert 11 13 0 05 Apr 2023
Feature Importance: A Closer Look at Shapley Values and LOCO I. Verdinelli Larry A. Wasserman FAtt TDI 23 20 0 10 Mar 2023
$Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of $\ell_2$ Regularization$ Individualized and Global Feature Attributions for Gradient Boosted Trees in the Presence of $\ell_2$ Regularization Qingyao Sun 26 2 0 08 Nov 2022
Abstract Interpretation-Based Feature Importance for SVMs Abhinanda Pal Francesco Ranzato Caterina Urban Marco Zanella FAtt 16 0 0 22 Oct 2022
DALE: Differential Accumulated Local Effects for efficient and accurate global explanations Vasilis Gkolemis Theodore Dalamagas Christos Diou 11 12 0 10 Oct 2022
Conditional Feature Importance for Mixed Data Kristin Blesch David S. Watson Marvin N. Wright 42 7 0 06 Oct 2022
Algorithm-Agnostic Interpretations for Clustering Christian A. Scholbeck Henri Funk Giuseppe Casalicchio 18 0 0 21 Sep 2022
Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams Fabian Fumagalli Maximilian Muschalik Eyke Hüllermeier Barbara Hammer 19 20 0 05 Sep 2022
Accelerated and interpretable oblique random survival forests Byron C. Jaeger Sawyer Welden K. Lenoir J. Speiser M. Segar A. Pandey N. Pajewski 14 15 0 01 Aug 2022
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence Isha Hameed Samuel Sharpe Daniel Barcklow Justin Au-yeung Sahil Verma Jocelyn Huang Brian Barr C. B. Bruss 30 14 0 12 Jul 2022
Do We Need Another Explainable AI Method? Toward Unifying Post-hoc XAI Evaluation Methods into an Interactive and Multi-dimensional Benchmark Mohamed Karim Belaid Eyke Hüllermeier Maximilian Rabus Ralf Krestel ELM 16 0 0 08 Jun 2022
Sequential Permutation Testing of Random Forest Variable Importance Measures Alexander Hapfelmeier R. Hornung Bernhard Haller 15 15 0 02 Jun 2022
Supervised Learning and Model Analysis with Compositional Data Shimeng Huang Elisabeth Ailer Niki Kilbertus Niklas Pfister 29 5 0 15 May 2022