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Relating the Partial Dependence Plot and Permutation Feature Importance
  to the Data Generating Process

Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process

3 September 2021
Christoph Molnar
Timo Freiesleben
Gunnar Konig
Giuseppe Casalicchio
Marvin N. Wright
B. Bischl
ArXiv (abs)PDFHTML

Papers citing "Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process"

16 / 16 papers shown
Title
Targeted Learning for Variable Importance
Targeted Learning for Variable Importance
Xiaohan Wang
Yunzhe Zhou
Giles Hooker
55
0
0
04 Nov 2024
Fast Estimation of Partial Dependence Functions using Trees
Fast Estimation of Partial Dependence Functions using Trees
Jinyang Liu
Tessa Steensgaard
Marvin N. Wright
Niklas Pfister
M. Hiabu
FAtt
112
0
0
17 Oct 2024
On the Robustness of Global Feature Effect Explanations
On the Robustness of Global Feature Effect Explanations
Hubert Baniecki
Giuseppe Casalicchio
Bernd Bischl
Przemyslaw Biecek
94
2
0
13 Jun 2024
Statistics and explainability: a fruitful alliance
Statistics and explainability: a fruitful alliance
Valentina Ghidini
51
0
0
30 Apr 2024
Why You Should Not Trust Interpretations in Machine Learning:
  Adversarial Attacks on Partial Dependence Plots
Why You Should Not Trust Interpretations in Machine Learning: Adversarial Attacks on Partial Dependence Plots
Xi Xin
Giles Hooker
Fei Huang
AAML
71
7
0
29 Apr 2024
mlr3summary: Concise and interpretable summaries for machine learning
  models
mlr3summary: Concise and interpretable summaries for machine learning models
Susanne Dandl
Marc Becker
B. Bischl
Giuseppe Casalicchio
Ludwig Bothmann
26
0
0
25 Apr 2024
A Guide to Feature Importance Methods for Scientific Inference
A Guide to Feature Importance Methods for Scientific Inference
F. K. Ewald
Ludwig Bothmann
Marvin N. Wright
B. Bischl
Giuseppe Casalicchio
Gunnar Konig
60
11
0
19 Apr 2024
Interpretable Machine Learning for Survival Analysis
Interpretable Machine Learning for Survival Analysis
Sophie Hanna Langbein
Mateusz Krzyzinski
Mikolaj Spytek
Hubert Baniecki
P. Biecek
Marvin N. Wright
85
2
0
15 Mar 2024
Innovations in Agricultural Forecasting: A Multivariate Regression Study
  on Global Crop Yield Prediction
Innovations in Agricultural Forecasting: A Multivariate Regression Study on Global Crop Yield Prediction
Ishaan Gupta
Samyutha Ayalasomayajula
Yashas Shashidhara
Anish Kataria
Shreyas Shashidhara
Krishita Kataria
Aditya Undurti
46
0
0
04 Dec 2023
RHALE: Robust and Heterogeneity-aware Accumulated Local Effects
RHALE: Robust and Heterogeneity-aware Accumulated Local Effects
Vasilis Gkolemis
Theodore Dalamagas
Eirini Ntoutsi
Christos Diou
41
5
0
20 Sep 2023
Confident Feature Ranking
Confident Feature Ranking
Bitya Neuhof
Y. Benjamini
FAtt
74
3
0
28 Jul 2023
Explaining and visualizing black-box models through counterfactual paths
Explaining and visualizing black-box models through counterfactual paths
Bastian Pfeifer
Mateusz Krzyzinski
Hubert Baniecki
Anna Saranti
Andreas Holzinger
P. Biecek
63
0
0
15 Jul 2023
Dear XAI Community, We Need to Talk! Fundamental Misconceptions in
  Current XAI Research
Dear XAI Community, We Need to Talk! Fundamental Misconceptions in Current XAI Research
Timo Freiesleben
Gunnar Konig
61
20
0
07 Jun 2023
Performance is not enough: the story told by a Rashomon quartet
Performance is not enough: the story told by a Rashomon quartet
P. Biecek
Hubert Baniecki
Mateusz Krzyzinski
Dianne Cook
46
9
0
26 Feb 2023
Model-Agnostic Confidence Intervals for Feature Importance: A Fast and
  Powerful Approach Using Minipatch Ensembles
Model-Agnostic Confidence Intervals for Feature Importance: A Fast and Powerful Approach Using Minipatch Ensembles
Luqin Gan
Lili Zheng
Genevera I. Allen
94
6
0
05 Jun 2022
Ultra-marginal Feature Importance: Learning from Data with Causal
  Guarantees
Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees
Joseph Janssen
Vincent Guan
Elina Robeva
66
7
0
21 Apr 2022
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