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Genetic Programming for Evolving a Front of Interpretable Models for
  Data Visualisation

Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation

IEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2020
27 January 2020
Andrew Lensen
Bing Xue
Mengjie Zhang
ArXiv (abs)PDFHTML

Papers citing "Genetic Programming for Evolving a Front of Interpretable Models for Data Visualisation"

15 / 15 papers shown
Evolutionary Computation and Explainable AI: A Roadmap to Transparent
  Intelligent Systems
Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems
Ryan Zhou
Jaume Bacardit
Alexander Brownlee
Stefano Cagnoni
Martin Fyvie
Giovanni Iacca
John Mccall
Niki van Stein
David Walker
Ting-Kuei Hu
235
1
0
12 Jun 2024
Explaining Genetic Programming Trees using Large Language Models
Explaining Genetic Programming Trees using Large Language Models
Paula Maddigan
Andrew Lensen
Bing Xue
AI4CE
173
10
0
06 Mar 2024
Evolving Genetic Programming Tree Models for Predicting the Mechanical
  Properties of Green Fibers for Better Biocomposite Materials
Evolving Genetic Programming Tree Models for Predicting the Mechanical Properties of Green Fibers for Better Biocomposite Materials
F. Al-Oqla
Hossam Faris
Maria Habib
Pedro Ángel Castillo Valdivieso
AI4CE
60
17
0
20 Feb 2024
Explainable Benchmarking for Iterative Optimization Heuristics
Explainable Benchmarking for Iterative Optimization Heuristics
Niki van Stein
Diederick Vermetten
Anna V. Kononova
Thomas Bäck
294
20
0
31 Jan 2024
Sampling - Variational Auto Encoder - Ensemble: In the Quest of
  Explainable Artificial Intelligence
Sampling - Variational Auto Encoder - Ensemble: In the Quest of Explainable Artificial Intelligence
S. Maitra
Vivek Mi̇shra
Pratima Verma
M. Chopra
Priyanka Nath
DRL
123
0
0
25 Sep 2023
Evolutionary approaches to explainable machine learning
Evolutionary approaches to explainable machine learning
Ryan Zhou
Ting-Kuei Hu
236
10
0
23 Jun 2023
A Survey on Distributed Evolutionary Computation
A Survey on Distributed Evolutionary ComputationIEEE Computational Intelligence Magazine (IEEE CIM), 2023
Wei Chen
Feng-Feng Wei
Tian-Fang Zhao
Kay Chen Tan
Jun Zhang
99
2
0
12 Apr 2023
Less is More: A Call to Focus on Simpler Models in Genetic Programming
  for Interpretable Machine Learning
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning
M. Virgolin
Eric Medvet
Tanja Alderliesten
Peter A. N. Bosman
153
6
0
05 Apr 2022
On genetic programming representations and fitness functions for
  interpretable dimensionality reduction
On genetic programming representations and fitness functions for interpretable dimensionality reductionAnnual Conference on Genetic and Evolutionary Computation (GECCO), 2022
Thomas Uriot
M. Virgolin
Tanja Alderliesten
Peter A. N. Bosman
196
9
0
01 Mar 2022
Genetic Programming for Manifold Learning: Preserving Local Topology
Genetic Programming for Manifold Learning: Preserving Local TopologyIEEE Transactions on Evolutionary Computation (TEVC), 2021
Andrew Lensen
Bing Xue
Mengjie Zhang
79
10
0
23 Aug 2021
Model Learning with Personalized Interpretability Estimation (ML-PIE)
Model Learning with Personalized Interpretability Estimation (ML-PIE)
M. Virgolin
A. D. Lorenzo
Francesca Randone
Eric Medvet
M. Wahde
381
33
0
13 Apr 2021
Mining Feature Relationships in Data
Mining Feature Relationships in DataEuropean Conference on Genetic Programming (EuroGP), 2021
Andrew Lensen
76
4
0
02 Feb 2021
Genetic Programming is Naturally Suited to Evolve Bagging Ensembles
Genetic Programming is Naturally Suited to Evolve Bagging Ensembles
M. Virgolin
383
0
0
13 Sep 2020
Interpretable Rule Discovery Through Bilevel Optimization of Split-Rules
  of Nonlinear Decision Trees for Classification Problems
Interpretable Rule Discovery Through Bilevel Optimization of Split-Rules of Nonlinear Decision Trees for Classification ProblemsIEEE Transactions on Cybernetics (IEEE Trans. Cybern.), 2020
Yashesh D. Dhebar
Kalyanmoy Deb
128
30
0
02 Aug 2020
Learning a Formula of Interpretability to Learn Interpretable Formulas
Learning a Formula of Interpretability to Learn Interpretable Formulas
M. Virgolin
A. D. Lorenzo
Eric Medvet
Francesca Randone
130
40
0
23 Apr 2020
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