Classification of vowels in continuous speech using MLP and a hybrid net
Speech Communication - Neurospeech
Machine Learning
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Symbolization assisted SVM classifier for noisy data
Pattern Recognition Letters
A comparison of SVM and HMM classifiers in the off-line signature verification
Pattern Recognition Letters
Global likelihood optimization via the cross-entropy method with an application to mixture models
WSC '04 Proceedings of the 36th conference on Winter simulation
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
A novel and quick SVM-based multi-class classifier
Pattern Recognition
Self-generating prototypes for pattern classification
Pattern Recognition
Facing classification problems with Particle Swarm Optimization
Applied Soft Computing
Survey of Improving K-Nearest-Neighbor for Classification
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
Expert Systems with Applications: An International Journal
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
Recognition of human activities using SVM multi-class classifier
Pattern Recognition Letters
BGSA: binary gravitational search algorithm
Natural Computing: an international journal
A novel clustering approach: Artificial Bee Colony (ABC) algorithm
Applied Soft Computing
Filter modeling using gravitational search algorithm
Engineering Applications of Artificial Intelligence
MIMO CMAC neural network classifier for solving classification problems
Applied Soft Computing
Projected-prototype based classifier for text categorization
Knowledge-Based Systems
A discrete gravitational search algorithm for solving combinatorial optimization problems
Information Sciences: an International Journal
Feature subset selection using improved binary gravitational search algorithm
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In recent years, heuristic algorithms have been successfully applied to solve clustering and classification problems. In this paper, gravitational search algorithm (GSA) which is one of the newest swarm based heuristic algorithms is used to provide a prototype classifier to face the classification of instances in multi-class data sets. The proposed method employs GSA as a global searcher to find the best positions of the representatives (prototypes). The proposed GSA-based classifier is used for data classification of some of the well-known benchmark sets. Its performance is compared with the artificial bee colony (ABC), the particle swarm optimization (PSO), and nine other classifiers from the literature. The experimental results of twelve data sets from UCI machine learning repository confirm that the GSA can successfully be applied as a classifier to classification problems.