Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms
@article{Zhao2014MultiobjectiveOO, title={Multiobjective optimization of classifiers by means of 3D convex-hull-based evolutionary algorithms}, author={Jiaqi Zhao and V{\'i}tor Basto Fernandes and Licheng Jiao and Iryna Yevseyeva and Asep Maulana and Rui Li and Thomas B{\"a}ck and Ke Tang and M. Emmerich}, journal={Inf. Sci.}, year={2014}, volume={367-368}, pages={80-104} }
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References
SHOWING 1-10 OF 78 REFERENCES
Convex Hull-Based Multiobjective Genetic Programming for Maximizing Receiver Operating Characteristic Performance
- Computer ScienceIEEE Transactions on Evolutionary Computation
- 2015
A new convex hull-based multiobjective genetic programming (CH-MOGP) is proposed to solve ROCCH maximization problems and it is hypothesized that by using a tailored indicator-based selection, CH-MogP becomes more efficient for ROC convex Hull approximation than algorithms that compute all Pareto optimal points.
Multi-objective genetic fuzzy classifiers for imbalanced and cost-sensitive datasets
- Computer ScienceSoft Comput.
- 2010
The FRBC selected from the convex hull produced by the three-objective optimization approach achieves the lowest classification cost among the techniques used as comparison in two specific medical applications.
A new multi-objective evolutionary algorithm based on convex hull for binary classifier optimization
- Computer Science2007 IEEE Congress on Evolutionary Computation
- 2007
A novel population- based multi-objective evolutionary algorithm (MOEA) for binary classifier optimization and how the Pareto front approximation generated by the proposed MOEA is better than the one generated by NSGA-II, one of the most known and used population-based MOEAs.
Multiobjective genetic programming for maximizing ROC performance
- Computer ScienceNeurocomputing
- 2014
Multi-class ROC analysis from a multi-objective optimisation perspective
- Computer SciencePattern Recognit. Lett.
- 2006
Multiobjective Genetic Optimization of Diagnostic Classifiers with Implications for Generating ROC Curves
- Computer ScienceIEEE Trans. Medical Imaging
- 1999
The authors have investigated the use of a niched Pareto multiobjective genetic algorithm (GA) for classifier optimization and applied this technique to train a linear classifier and an artificial neural network, using simulated datasets.
A multi-model selection framework for unknown and/or evolutive misclassification cost problems
- Computer SciencePattern Recognit.
- 2010
Volume under the ROC Surface for Multi-class Problems
- Computer Science, MathematicsECML
- 2003
This paper presents the real extension to the Area Under the AUC Curve in the form of the Volume Under the ROC Surface (VUS), showing how to compute the polytope that corresponds to the absence of classifiers, to the best classifier and to whatever set of classifier.
Evolving Neural Networks with Maximum AUC for Imbalanced Data Classification
- Computer ScienceHAIS
- 2010
Empirical studies show that the proposed evolutionary AUC maximization (EAM) method can train NN with larger AUC than existing methods.
A multi-objective genetic programming approach to developing Pareto optimal decision trees
- Computer ScienceDecis. Support Syst.
- 2007