Explainable artificial intelligence by genetic programming: A survey
Explainable artificial intelligence (XAI) has received great interest in the recent decade, due
to its importance in critical application domains, such as self-driving cars, law, and …
to its importance in critical application domains, such as self-driving cars, law, and …
Operator equalisation for bloat free genetic programming and a survey of bloat control methods
S Silva, S Dignum, L Vanneschi - Genetic Programming and Evolvable …, 2012 - Springer
Bloat can be defined as an excess of code growth without a corresponding improvement in
fitness. This problem has been one of the most intensively studied subjects since the …
fitness. This problem has been one of the most intensively studied subjects since the …
[HTML][HTML] Early stopping by correlating online indicators in neural networks
In order to minimize the generalization error in neural networks, a novel technique to identify
overfitting phenomena when training the learner is formally introduced. This enables support …
overfitting phenomena when training the learner is formally introduced. This enables support …
Feature selection to improve generalization of genetic programming for high-dimensional symbolic regression
When learning from high-dimensional data for symbolic regression (SR), genetic
programming (GP) typically could not generalize well. Feature selection, as a data …
programming (GP) typically could not generalize well. Feature selection, as a data …
Open issues in genetic programming
It is approximately 50 years since the first computational experiments were conducted in
what has become known today as the field of Genetic Programming (GP), twenty years since …
what has become known today as the field of Genetic Programming (GP), twenty years since …
[HTML][HTML] Deep learning models for real-life human activity recognition from smartphone sensor data
Nowadays, the field of human activity recognition (HAR) is a remarkably hot topic within the
scientific community. Given the low cost, ease of use and high accuracy of the sensors from …
scientific community. Given the low cost, ease of use and high accuracy of the sensors from …
Forecasting personal learning performance in virtual reality-based construction safety training using biometric responses
During virtual reality-based safety training, it is necessary to immediately and objectively
evaluate personal learning performance. In light of this, this study proposed an interpretable …
evaluate personal learning performance. In light of this, this study proposed an interpretable …
Rademacher complexity for enhancing the generalization of genetic programming for symbolic regression
Model complexity has a close relationship with the generalization ability and the
interpretability of the learned models. Simple models are more likely to generalize well and …
interpretability of the learned models. Simple models are more likely to generalize well and …
Multi-generation multi-criteria feature construction using genetic programming
J Ma, X Gao, Y Li - Swarm and Evolutionary Computation, 2023 - Elsevier
The purpose of feature construction is to create new high level features from the original
features. When Genetic Programming (GP) is applied to wrapper-based feature construction …
features. When Genetic Programming (GP) is applied to wrapper-based feature construction …
Learning a formula of interpretability to learn interpretable formulas
Many risk-sensitive applications require Machine Learning (ML) models to be interpretable.
Attempts to obtain interpretable models typically rely on tuning, by trial-and-error, hyper …
Attempts to obtain interpretable models typically rely on tuning, by trial-and-error, hyper …