Cover Image

A Novel Machine Learning Classifier Based on Genetic Algorithms and Data Importance Reformatting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Alkhayyata, A. K., Hewahi, N. M.
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Genetic Algorithm-Based Approach for Automated Optimization of Kolmogorov-Arnold Networks in Classification Tasks
by: Long, Quan, et al.
Published: (2025)

MeGA: Merging Multiple Independently Trained Neural Networks Based on Genetic Algorithm
by: Yun, Daniel
Published: (2024)

Novel Deep Neural Network Classifier Characterization Metrics with Applications to Dataless Evaluation
by: Dean, Nathaniel, et al.
Published: (2024)

Fast Genetic Algorithm for feature selection -- A qualitative approximation approach
by: Altarabichi, Mohammed Ghaith, et al.
Published: (2024)

Enhancing Genetic Algorithms with Graph Neural Networks: A Timetabling Case Study
by: Cornei, Laura-Maria, et al.
Published: (2026)

Multi-Objective Genetic Algorithm for Multi-View Feature Selection
by: Imani, Vandad, et al.
Published: (2023)

EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs
by: Yuksel, Kamer Ali, et al.
Published: (2026)

A Class Inference Scheme With Dempster-Shafer Theory for Learning Fuzzy-Classifier Systems
by: Shiraishi, Hiroki, et al.
Published: (2025)

GenPluSSS: A Genetic Algorithm Based Plugin for Measured Subsurface Scattering Representation
by: Yıldırım, Barış, et al.
Published: (2024)

Small Contributions, Small Networks: Efficient Neural Network Pruning Based on Relative Importance
by: Hussien, Mostafa, et al.
Published: (2024)

Adapting Rule Representation With Four-Parameter Beta Distribution for Learning Classifier Systems
by: Shiraishi, Hiroki, et al.
Published: (2025)

Reinforcement Learning-assisted Evolutionary Algorithm: A Survey and Research Opportunities
by: Song, Yanjie, et al.
Published: (2023)

Unveiling the Decision-Making Process in Reinforcement Learning with Genetic Programming
by: Eberhardinger, Manuel, et al.
Published: (2024)

On the Temperature of Machine Learning Systems
by: Zhang, Dong
Published: (2024)

SkipSNN: Efficiently Classifying Spike Trains with Event-attention
by: Yin, Hang, et al.
Published: (2024)

Fitness Approximation through Machine Learning
by: Tzruia, Itai, et al.
Published: (2023)

A Firefly Algorithm for Mixed-Variable Optimization Based on Hybrid Distance Modeling
by: Bechir, Ousmane Tom, et al.
Published: (2026)

Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling
by: Loo, Junn Yong, et al.
Published: (2024)

Genetic Generalized Additive Models
by: Shankar, Kaaustaaub, et al.
Published: (2026)

A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
by: Salvatori, Tommaso, et al.
Published: (2022)

Mechanistic Neural Networks for Scientific Machine Learning
by: Pervez, Adeel, et al.
Published: (2024)

A Novel Reservoir Computing Framework for Chaotic Time Series Prediction Using Time Delay Embedding and Random Fourier Features
by: Laha, S. K.
Published: (2025)

Introduction to Predictive Coding Networks for Machine Learning
by: Stenlund, Mikko
Published: (2025)

An Experimental Study on Decomposition-Based Deep Ensemble Learning for Traffic Flow Forecasting
by: Zhu, Qiyuan, et al.
Published: (2024)

An Inverse Modeling Constrained Multi-Objective Evolutionary Algorithm Based on Decomposition
by: Farias, Lucas R. C., et al.
Published: (2024)

Dynamic Design of Machine Learning Pipelines via Metalearning
by: Alcobaça, Edesio, et al.
Published: (2025)

Knowing When to Stop: Delay-Adaptive Spiking Neural Network Classifiers with Reliability Guarantees
by: Chen, Jiechen, et al.
Published: (2023)

Evaluating the Robustness of Deep-Learning Algorithm-Selection Models by Evolving Adversarial Instances
by: Hart, Emma, et al.
Published: (2024)

Cartesian Genetic Programming Approach for Designing Convolutional Neural Networks
by: Krzywda, Maciej, et al.
Published: (2024)

Node Preservation and its Effect on Crossover in Cartesian Genetic Programming
by: Kocherovsky, Mark, et al.
Published: (2025)

Experimental Evaluation of Machine Learning Models for Goal-oriented Customer Service Chatbot with Pipeline Architecture
by: Isa, Nurul Ain Nabilah Mohd, et al.
Published: (2024)

Optimizing PM2.5 Forecasting Accuracy with Hybrid Meta-Heuristic and Machine Learning Models
by: Ghafariasl, Parviz, et al.
Published: (2024)

The Enduring Dominance of Deep Neural Networks: A Critical Analysis of the Fundamental Limitations of Quantum Machine Learning and Spiking Neural Networks
by: Ishikawa, Takehiro
Published: (2025)

EvoSyn: Generalizable Evolutionary Data Synthesis for Verifiable Learning
by: Du, He, et al.
Published: (2025)

Offline Model-Based Optimization by Learning to Rank
by: Tan, Rong-Xi, et al.
Published: (2024)

Real-time Noise Detection and Classification in Single-Channel EEG: A Lightweight Machine Learning Approach for EMG, White Noise, and EOG Artifacts
by: Enshaei, Hossein, et al.
Published: (2025)

Parallel Algorithms for Exact Enumeration of Deep Neural Network Activation Regions
by: Drammis, Sabrina, et al.
Published: (2024)

A Learning-Based Cooperative Coevolution Framework for Heterogeneous Large-Scale Global Optimization
by: Qiu, Wenjie, et al.
Published: (2026)

Projective Kolmogorov Arnold Neural Networks (P-KANs): Entropy-Driven Functional Space Discovery for Interpretable Machine Learning
by: Poole, Alastair, et al.
Published: (2025)

Automated Algorithm Design for Auto-Tuning Optimizers
by: Willemsen, Floris-Jan, et al.
Published: (2025)