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

Explainable Artificial Intelligence, p.456-479

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Visualizing the Feature Importance for Black Box Models

Machine Learning and Knowledge Discovery in Databases, p.655-670

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Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach

Data mining and knowledge discovery, 2024-09, Vol.38 (5), p.2903-2941

2024

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Grouped feature importance and combined features effect plot

Data mining and knowledge discovery, 2022-07, Vol.36 (4), p.1401-1450

2022

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Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability

Machine Learning and Knowledge Discovery in Databases, p.193-204

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Marginal effects for non-linear prediction functions

Data mining and knowledge discovery, 2024-09, Vol.38 (5), p.2997-3042

2024

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Correction: Marginal effects for non-linear prediction functions

Data mining and knowledge discovery, 2024-11, Vol.38 (6), p.4234-4235

2024

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Nonlinear Analysis to Detect if Excellent Nursing Work Environments Have Highest Well‐Being

Journal of nursing scholarship, 2017-09, Vol.49 (5), p.537-547

2017

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OpenML: An R package to connect to the machine learning platform OpenML

Computational statistics, 2019-09, Vol.34 (3), p.977-991

2019

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Over‐optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results

Wiley interdisciplinary reviews. Data mining and knowledge discovery, 2022-03, Vol.12 (2), p.e1441-n/a

2022

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Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations

Machine Learning and Knowledge Discovery in Databases, p.205-216

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On benchmark experiments and visualization methods for the evaluation and interpretation of machine learning models

Casalicchio, Giuseppe

2019

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Multilabel Classification with R Package mlr

The R journal, 2017-06, Vol.9 (1), p.352

2017

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Interpretable Regional Descriptors: Hyperbox-Based Local Explanations

Machine Learning and Knowledge Discovery in Databases: Research Track, p.479-495

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Subject-specific Bradley–Terry–Luce models with implicit variable selection

Statistical modelling, 2015-12, Vol.15 (6), p.526-547

2015

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The residual-based predictiveness curve: A visual tool to assess the performance of prediction models

Biometrics, 2016-06, Vol.72 (2), p.392-401

2016

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On the Robustness of Global Feature Effect Explanations

Machine Learning and Knowledge Discovery in Databases. Research Track, p.125-142

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Algorithm-Agnostic Feature Attributions for Clustering

Explainable Artificial Intelligence, p.217-240

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A Guide to Feature Importance Methods for Scientific Inference

Explainable Artificial Intelligence, p.440-464

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mlr3: A modern object-oriented machine learning framework in R

Journal of open source software, 2019-12, Vol.4 (44), p.1903

2019

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Evaluation and Benchmarking

Applied Machine Learning Using mlr3 in R, 2024, Vol.1, p.53-82

1, 2024

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Effects of the housing climate on the foot pad health of fattening turkeys of British United Turkeys 6 origin during the early rearing phase

Berliner und Münchener tierärztliche Wochenschrift, 2013-05, Vol.126 (5-6), p.181

2013

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Model Interpretation

Applied Machine Learning Using mlr3 in R, 2024, Vol.1, p.259-282

1, 2024

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Interpretable Machine Learning – A Brief History, State-of-the-Art and Challenges

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

Visualizing the Feature Importance for Black Box Models

Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach

Grouped feature importance and combined features effect plot

Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability

Marginal effects for non-linear prediction functions

Correction: Marginal effects for non-linear prediction functions

Nonlinear Analysis to Detect if Excellent Nursing Work Environments Have Highest Well‐Being

OpenML: An R package to connect to the machine learning platform OpenML

Over‐optimism in benchmark studies and the multiplicity of design and analysis options when interpreting their results

Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations

On benchmark experiments and visualization methods for the evaluation and interpretation of machine learning models

Multilabel Classification with R Package mlr

Interpretable Regional Descriptors: Hyperbox-Based Local Explanations

Subject-specific Bradley–Terry–Luce models with implicit variable selection

The residual-based predictiveness curve: A visual tool to assess the performance of prediction models

On the Robustness of Global Feature Effect Explanations

Algorithm-Agnostic Feature Attributions for Clustering

Leveraging Model-Based Trees as Interpretable Surrogate Models for Model Distillation

A Guide to Feature Importance Methods for Scientific Inference

mlr3: A modern object-oriented machine learning framework in R

Evaluation and Benchmarking

Effects of the housing climate on the foot pad health of fattening turkeys of British United Turkeys 6 origin during the early rearing phase

Model Interpretation

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