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Shapley variable importance clouds for interpretable machine learning

Shapley variable importance clouds for interpretable machine learning

6 October 2021
Yilin Ning
M. Ong
Bibhas Chakraborty
B. Goldstein
Daniel Ting
Roger Vaughan
Nan Liu
    FAtt
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Papers citing "Shapley variable importance clouds for interpretable machine learning"

5 / 5 papers shown
Title
Evaluating AI fairness in credit scoring with the BRIO tool
Evaluating AI fairness in credit scoring with the BRIO tool
Greta Coraglia
Francesco Genco
Pellegrino Piantadosi
Enrico Bagli
Pietro Giuffrida
Davide Posillipo
Giuseppe Primiero
29
1
0
05 Jun 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
30
10
0
19 Apr 2024
Hypothesis Testing and Machine Learning: Interpreting Variable Effects
  in Deep Artificial Neural Networks using Cohen's f2
Hypothesis Testing and Machine Learning: Interpreting Variable Effects in Deep Artificial Neural Networks using Cohen's f2
Wolfgang Messner
CML
8
12
0
02 Feb 2023
Shapley variable importance cloud for machine learning models
Shapley variable importance cloud for machine learning models
Yilin Ning
Mingxuan Liu
Nan Liu
FAtt
TDI
30
1
0
16 Dec 2022
A novel interpretable machine learning system to generate clinical risk
  scores: An application for predicting early mortality or unplanned
  readmission in a retrospective cohort study
A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study
Yilin Ning
Siqi Li
M. Ong
F. Xie
Bibhas Chakraborty
Daniel Ting
Nan Liu
FAtt
11
22
0
10 Jan 2022
1