Feature subset selection using improved binary gravitational search algorithm

Authors:
Esmat Rashedi;Hossein Nezamabadi-pour
Affiliations:
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran;Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Year:
2014

Citing 33
Cited 0

SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries

IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Feature Selection Applied to Content-Based Retrieval of Lung Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Representations and Feature Selection for Multimedia Database Search

IEEE Transactions on Knowledge and Data Engineering
An introduction to variable and feature selection

The Journal of Machine Learning Research
Hybrid Genetic Algorithms for Feature Selection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward Integrating Feature Selection Algorithms for Classification and Clustering

IEEE Transactions on Knowledge and Data Engineering
Rapid and brief communication: Eliminating redundancy and irrelevance using a new MLP-based feature selection method

Pattern Recognition
A Niching Memetic Algorithm for Simultaneous Clustering and Feature Selection

IEEE Transactions on Knowledge and Data Engineering
Particle swarm optimization for parameter determination and feature selection of support vector machines

Expert Systems with Applications: An International Journal
A distributed PSO-SVM hybrid system with feature selection and parameter optimization

Applied Soft Computing
A GA-Based Feature Subset Selection and Parameter Optimization of Support Vector Machine for Content --- Based Image Retrieval

ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
GSA: A Gravitational Search Algorithm

Information Sciences: an International Journal
Feature selection for SVM via optimization of kernel polarization with Gaussian ARD kernels

Expert Systems with Applications: An International Journal
BGSA: binary gravitational search algorithm

Natural Computing: an international journal
Chaotic maps based on binary particle swarm optimization for feature selection

Applied Soft Computing
A novel image retrieval model based on the most relevant features

Knowledge-Based Systems
Simultaneous feature selection and classification using kernel-penalized support vector machines

Information Sciences: an International Journal
Feature selection using genetic algorithm and cluster validation

Expert Systems with Applications: An International Journal
Filter modeling using gravitational search algorithm

Engineering Applications of Artificial Intelligence
A Multi-objective Gravitational Search Algorithm

CICSYN '10 Proceedings of the 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks
Applying electromagnetism-like mechanism for feature selection

Information Sciences: an International Journal
A GRASP algorithm for fast hybrid (filter-wrapper) feature subset selection in high-dimensional datasets

Pattern Recognition Letters
Feature subset selection using differential evolution and a statistical repair mechanism

Expert Systems with Applications: An International Journal
Core-generating approximate minimum entropy discretization for rough set feature selection in pattern classification

International Journal of Approximate Reasoning
mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

Information Sciences: an International Journal
A new hybrid ant colony optimization algorithm for feature selection

Expert Systems with Applications: An International Journal
A prototype classifier based on gravitational search algorithm

Applied Soft Computing
Orthogonal forward selection and backward elimination algorithms for feature subset selection

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A new local search based hybrid genetic algorithm for feature selection

Neurocomputing
Similarity-based online feature selection in content-based image retrieval

IEEE Transactions on Image Processing
Overview of the MPEG-7 standard

IEEE Transactions on Circuits and Systems for Video Technology
Attribute selection based on information gain ratio in fuzzy rough set theory with application to tumor classification

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Feature selection is one of the important activities in various fields such as computer vision and pattern recognition. In this paper, an improved version of the binary gravitational search algorithm BGSA is proposed and used as a tool to select the best subset of features with the goal of improving classification accuracy. By enhancing the transfer function, we give BGSA the ability to overcome the stagnation situation. This allows the search algorithm to explore a larger group of possibilities and avoid stagnation. To evaluate the proposed improved BGSA IBGSA, classification of some well known datasets and improving the accuracy of CBIR systems are experienced. Results are compared with those of original BGSA, genetic algorithm GA, binary particle swarm optimization BPSO, and electromagnetic-like mechanism. Comparative results confirm the effectiveness of the proposed IBGSA in feature selection.