African buffalo algorithm: Training the probabilistic neural network to solve classification problems
Sign Up to like & getrecommendations! Published in 2020 at "Journal of King Saud University - Computer and Information Sciences"
DOI: 10.1016/j.jksuci.2020.07.004
Abstract: Abstract Classification is used to categorize data and produce decisions for several domains. To improve the accuracy of classification, researchers have tended to hybridize the neural network with other metaheuristic algorithms in order to better… read more here.
Keywords: classification; algorithm; classification problems; neural network ... See more keywords
Evolutionary Spiking Neural Networks for Solving Supervised Classification Problems
Sign Up to like & getrecommendations! Published in 2019 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2019/4182639
Abstract: This paper presents a grammatical evolution (GE)-based methodology to automatically design third generation artificial neural networks (ANNs), also known as spiking neural networks (SNNs), for solving supervised classification problems. The proposal performs the SNN design… read more here.
Keywords: methodology; solving supervised; neural networks; supervised classification ... See more keywords
Incorporating Grey Total Influence into Tolerance Rough Sets for Classification Problems
Sign Up to like & getrecommendations! Published in 2018 at "Applied Sciences"
DOI: 10.3390/app8071173
Abstract: Tolerance-rough-set-based classifiers (TRSCs) are known to operate effectively on real-valued attributes for classification problems. This involves creating a tolerance relation that is defined by a distance function to estimate proximity between any pair of patterns.… read more here.
Keywords: classification; tolerance; tolerance rough; total influence ... See more keywords
Minimizing features while maintaining performance in data classification problems
Sign Up to like & getrecommendations! Published in 2022 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.1081
Abstract: High dimensional classification problems have gained increasing attention in machine learning, and feature selection has become essential in executing machine learning algorithms. In general, most feature selection methods compare the scores of several feature subsets… read more here.
Keywords: classification; feature; classification problems; feature selection ... See more keywords