Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms

@article{Xue2014ParticleSO,
  title={Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms},
  author={Bing Xue and M. Zhang and W. Browne},
  journal={Appl. Soft Comput.},
  year={2014},
  volume={18},
  pages={261-276}
}
  • Bing Xue, M. Zhang, W. Browne
  • Published 2014
  • Computer Science
  • Appl. Soft Comput.
  • In classification, feature selection is an important data pre-processing technique, but it is a difficult problem due mainly to the large search space. Particle swarm optimisation (PSO) is an efficient evolutionary computation technique. However, the traditional personal best and global best updating mechanism in PSO limits its performance for feature selection and the potential of PSO for feature selection has not been fully investigated. This paper proposes three new initialisation strategies… CONTINUE READING
    295 Citations
    New efficient initialization and updating mechanisms in PSO for feature selection and classification
    • 1
    • Highly Influenced
    Particle Swarm Optimisation with genetic operators for feature selection
    • 15
    Efficient Feature Selection Algorithm Based on Particle Swarm Optimization With Learning Memory
    • 5
    • Highly Influenced
    • PDF
    A Particle Swarm Optimization with Filter-based Population Initialization for Feature Selection
    Overview of Particle Swarm Optimisation for Feature Selection in Classification
    • 30
    • PDF
    New mechanism for archive maintenance in PSO-based multi-objective feature selection
    • 20
    • PDF

    References

    SHOWING 1-10 OF 57 REFERENCES
    Novel Initialisation and Updating Mechanisms in PSO for Feature Selection in Classification
    • 37
    • PDF
    Multi-objective particle swarm optimisation (PSO) for feature selection
    • 69
    • PDF
    Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach
    • 639
    • PDF
    New fitness functions in binary particle swarm optimisation for feature selection
    • 59
    • PDF
    Feature selection based on rough sets and particle swarm optimization
    • 739
    • PDF
    An Improved Particle Swarm Optimization with an Adaptive Updating Mechanism
    • 2
    PSOLDA: A particle swarm optimization approach for enhancing classification accuracy rate of linear discriminant analysis
    • 60
    • Highly Influential
    • PDF
    Improved binary particle swarm optimization using catfish effect for feature selection
    • 178
    • Highly Influential
    • PDF
    Adaptive Particle Swarm Optimizer for Feature Selection
    • 19
    A rough set approach to feature selection based on ant colony optimization
    • 251
    • PDF