Developing New Fitness Functions in Genetic Programming for Classification With Unbalanced Data

@article{Bhowan2012DevelopingNF,
  title={Developing New Fitness Functions in Genetic Programming for Classification With Unbalanced Data},
  author={Urvesh Bhowan and M. Johnston and M. Zhang},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
  year={2012},
  volume={42},
  pages={406-421}
}
  • Urvesh Bhowan, M. Johnston, M. Zhang
  • Published 2012
  • Computer Science, Medicine
  • IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)
  • Machine learning algorithms such as genetic programming (GP) can evolve biased classifiers when data sets are unbalanced. Data sets are unbalanced when at least one class is represented by only a small number of training examples (called the minority class) while other classes make up the majority. In this scenario, classifiers can have good accuracy on the majority class but very poor accuracy on the minority class(es) due to the influence that the larger majority class has on traditional… CONTINUE READING
    83 Citations
    New Fitness Functions in Genetic Programming for Classification with High-dimensional Unbalanced Data
    • 4
    A Cost-sensitive Genetic Programming Approach for High-dimensional Unbalanced Classification
    • 2
    • Highly Influenced
    Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data
    • 49
    • PDF
    A Threshold-free Classification Mechanism in Genetic Programming for High-dimensional Unbalanced Classification
    • 1
    • Highly Influenced
    • PDF
    A Multiobjective Genetic Programming-Based Ensemble for Simultaneous Feature Selection and Classification
    • K. Nag, N. Pal
    • Mathematics, Computer Science
    • IEEE Transactions on Cybernetics
    • 2016
    • 96
    • PDF
    A Survey of Methods for Managing the Classification and Solution of Data Imbalance Problem
    • PDF

    References

    SHOWING 1-10 OF 69 REFERENCES
    Differentiating between individual class performance in Genetic Programming fitness for classification with unbalanced data
    • 18
    • PDF
    Fitness Functions in Genetic Programming for Classification with Unbalanced Data
    • 57
    A Comparison of Classification Strategies in Genetic Programming with Unbalanced Data
    • 10
    • PDF
    GP Classification under Imbalanced Data sets: Active Sub-sampling and AUC Approximation
    • 59
    • Highly Influential
    • PDF
    Evolving ensembles in multi-objective genetic programming for classification with unbalanced data
    • 22
    Class imbalance problem in UCS classifier system: fitness adaptation
    • 39
    • Highly Influential
    • PDF
    Representing classification problems in genetic programming
    • 211
    • PDF
    Ensemble Approach for the Classification of Imbalanced Data
    • 22
    • PDF
    Advanced Genetic Programming Based Machine Learning
    • 33