Survivor selection in a crossoverless evolutionary algorithm

Brouwer, Nielis; Dijkzeul, Danny; Koppenhol, Levi; Pijning, Iris; Berg, Daan van den

doi:10.1145/3520304.3533950

Cited by 4 publications

(3 citation statements)

References 30 publications

(59 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From a review by [38], out of eight selection methods available, three of it are elitist based method that always include the best individual in the new population. When using an elitist method, the best fitness in the population cannot decrease over time [38,39,40].…”

Section: Optimized Svm-ga Algorithmmentioning

confidence: 99%

An Optimized Support Vector Machine With Genetic Algorithm for Imbalanced Data Classification

Shamsudin,

Yusof,

Haijie

et al. 2023

Jurnal Teknologi

View full text Add to dashboard Cite

In supervised machine learning, class imbalance is commonly occurring when the number of examples that represent one class is much lower than other classes. Since an imbalance data may generate suboptimal classification models, it could lead to the minority examples are misclassified frequently and hardly achieving the best performance. This study proposes an improved support vector machine (SVM) method for imbalanced data namely as SVM-GA by optimizing SVM algorithm with Genetic Algorithm (GA) over a synthetic minority oversampling technique. Besides considering the best sampling method in optimized SVM, the experimental result shows that the proposed method improves by 97% compared to the baseline model and selected optimized models. The proposed model had significant performance by outperformed the baseline model and other models based SVM with Grid search and Randomized search in most of the cases, especially for the datasets which have extremely rare cases.

show abstract

Section: Optimized Svm-ga Algorithmmentioning

confidence: 99%

An Optimized Support Vector Machine With Genetic Algorithm for Imbalanced Data Classification

Shamsudin,

Yusof,

Haijie

et al. 2023

Jurnal Teknologi

View full text Add to dashboard Cite

show abstract

“…Thereby, the top (individual's) objective value in the population can never deteriorate, and the method can be considered an elitist algorithm. Whether this selection method is actually the best is open for discussion, as Nielis Brouwer's recent investigation suggests elitist tournament selection performs better -be it on continuous benchmark functions [8]. But plus-selection is the seminal selection method which for now, we shall adhere to.…”

Section: Plant Propagation Algorithmmentioning

confidence: 99%

“…Even just changing the dimensionality gave rise to different and non-trivial results [14]. A study by Nielis Brouwer investigated alternative survivor selection methods for the same continuous benchmark functions as in Vrielink's and De Jonge's studies, and contrastive to Nannen, Smit and Eiben's study, changing this operator made a great difference in PPA's performance [8].…”

Section: Ppa and Parametersmentioning

confidence: 99%

Exactly characterizable parameter settings in a crossoverless evolutionary algorithm

Koppenhol

Brouwer

Dijkzeul

et al. 2022

Proceedings of the Genetic and Evolutionary Computation Conference Companion

Self Cite

View full text Add to dashboard Cite

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

show abstract