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Post-hoc explanation of black-box classifiers using confident itemsets

Post-hoc explanation of black-box classifiers using confident itemsets

5 May 2020
M. Moradi
Matthias Samwald
ArXivPDFHTML

Papers citing "Post-hoc explanation of black-box classifiers using confident itemsets"

21 / 21 papers shown
Title
Analyzing Factors Influencing Driver Willingness to Accept Advanced Driver Assistance Systems
Hannah Musau
Nana Kankam Gyimah
Judith Mwakalonge
G. Comert
Saidi Siuhi
34
0
0
23 Feb 2025
Fast Calibrated Explanations: Efficient and Uncertainty-Aware
  Explanations for Machine Learning Models
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning Models
Tuwe Löfström
Fatima Rabia Yapicioglu
Alessandra Stramiglio
Helena Lofstrom
Fabio Vitali
FAtt
LRM
32
0
0
28 Oct 2024
Ensured: Explanations for Decreasing the Epistemic Uncertainty in
  Predictions
Ensured: Explanations for Decreasing the Epistemic Uncertainty in Predictions
Helena Lofstrom
Tuwe Löfström
Johan Hallberg Szabadvary
28
0
0
07 Oct 2024
Developing Guidelines for Functionally-Grounded Evaluation of
  Explainable Artificial Intelligence using Tabular Data
Developing Guidelines for Functionally-Grounded Evaluation of Explainable Artificial Intelligence using Tabular Data
M. Velmurugan
Chun Ouyang
Yue Xu
Renuka Sindhgatta
B. Wickramanayake
Catarina Moreira
ELM
LMTD
XAI
14
0
0
30 Sep 2024
On the Definition of Appropriate Trust and the Tools that Come with it
On the Definition of Appropriate Trust and the Tools that Come with it
Helena Löfström
11
1
0
21 Sep 2023
Calibrated Explanations for Regression
Calibrated Explanations for Regression
Tuwe Löfström
Helena Lofstrom
Ulf Johansson
Cecilia Sönströd
Rudy Matela
XAI
FAtt
6
2
0
30 Aug 2023
CLIMAX: An exploration of Classifier-Based Contrastive Explanations
CLIMAX: An exploration of Classifier-Based Contrastive Explanations
Praharsh Nanavati
Ranjitha Prasad
19
0
0
02 Jul 2023
Calibrated Explanations: with Uncertainty Information and
  Counterfactuals
Calibrated Explanations: with Uncertainty Information and Counterfactuals
Helena Lofstrom
Tuwe Lofstrom
Gregory Rice
Cecilia Sonstrod
33
9
0
03 May 2023
Model-agnostic explainable artificial intelligence for object detection
  in image data
Model-agnostic explainable artificial intelligence for object detection in image data
M. Moradi
Ke Yan
David Colwell
Matthias Samwald
Rhona Asgari
AAML
33
7
0
30 Mar 2023
A Survey on Explainable Artificial Intelligence for Cybersecurity
A Survey on Explainable Artificial Intelligence for Cybersecurity
Gaith Rjoub
Jamal Bentahar
Omar Abdel Wahab
R. Mizouni
Alyssa Song
Robin Cohen
Hadi Otrok
Azzam Mourad
6
27
0
07 Mar 2023
Causality-Aware Local Interpretable Model-Agnostic Explanations
Causality-Aware Local Interpretable Model-Agnostic Explanations
Martina Cinquini
Riccardo Guidotti
CML
31
0
0
10 Dec 2022
ESC-Rules: Explainable, Semantically Constrained Rule Sets
ESC-Rules: Explainable, Semantically Constrained Rule Sets
Martin Glauer
Robert West
S. Michie
Janna Hastings
8
3
0
26 Aug 2022
Efficient Learning of Interpretable Classification Rules
Efficient Learning of Interpretable Classification Rules
Bishwamittra Ghosh
Dmitry Malioutov
Kuldeep S. Meel
9
7
0
14 May 2022
A Meta Survey of Quality Evaluation Criteria in Explanation Methods
A Meta Survey of Quality Evaluation Criteria in Explanation Methods
Helena Lofstrom
K. Hammar
Ulf Johansson
XAI
20
11
0
25 Mar 2022
Deep Learning, Natural Language Processing, and Explainable Artificial
  Intelligence in the Biomedical Domain
Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain
M. Moradi
Matthias Samwald
33
7
0
25 Feb 2022
Visual Exploration of Machine Learning Model Behavior with Hierarchical
  Surrogate Rule Sets
Visual Exploration of Machine Learning Model Behavior with Hierarchical Surrogate Rule Sets
Jun Yuan
Brian Barr
Kyle Overton
E. Bertini
6
8
0
19 Jan 2022
Improving the robustness and accuracy of biomedical language models
  through adversarial training
Improving the robustness and accuracy of biomedical language models through adversarial training
M. Moradi
Matthias Samwald
AAML
OOD
MedIm
31
10
0
16 Nov 2021
Evaluating the Robustness of Neural Language Models to Input
  Perturbations
Evaluating the Robustness of Neural Language Models to Input Perturbations
M. Moradi
Matthias Samwald
AAML
37
95
0
27 Aug 2021
Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey
Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey
Thomas Rojat
Raphael Puget
David Filliat
Javier Del Ser
R. Gelin
Natalia Díaz Rodríguez
XAI
AI4TS
21
126
0
02 Apr 2021
Explaining Black-box Models for Biomedical Text Classification
Explaining Black-box Models for Biomedical Text Classification
M. Moradi
Matthias Samwald
23
21
0
20 Dec 2020
Explaining black-box text classifiers for disease-treatment information
  extraction
Explaining black-box text classifiers for disease-treatment information extraction
M. Moradi
Matthias Samwald
30
2
0
21 Oct 2020
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