The Strength of Weak Learnability
Machine Learning
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Machine Learning
Machine Learning
The Random Subspace Method for Constructing Decision Forests
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Boosting the margin: A new explanation for the effectiveness of voting methods
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Combining Pattern Classifiers: Methods and Algorithms
Combining Pattern Classifiers: Methods and Algorithms
Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining (Advanced Information Processing)
A Mathematical Theory of Communication
A Mathematical Theory of Communication
A Comparison of Decision Tree Ensemble Creation Techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Boosting fuzzy rules in classification problems under single-winner inference: Research Articles
International Journal of Intelligent Systems
Engineering multiversion neural-net systems
Neural Computation
Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers
International Journal of Hybrid Intelligent Systems - Hybrid Intelligent systems in Ensembles
Genetic rule selection with a multi-classifier coding scheme for ensemble classifier design
International Journal of Hybrid Intelligent Systems - Hybridization of Intelligent Systems
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Genetic algorithms in classifier fusion
Applied Soft Computing
Classifier subset selection for biomedical named entity recognition
Applied Intelligence
A proposal on reasoning methods in fuzzy rule-based classification systems
International Journal of Approximate Reasoning
Selecting diversifying heuristics for cluster ensembles
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
Selection of decision stumps in bagging ensembles
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Multi-objective genetic algorithms to create ensemble of classifiers
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Boosting ensemble of relational neuro-fuzzy systems
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Evolutionary ensembles with negative correlation learning
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Ensembling local learners ThroughMultimodal perturbation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Induction of fuzzy-rule-based classifiers with evolutionary boosting algorithms
IEEE Transactions on Fuzzy Systems
Analysis of bagging ensembles of fuzzy models for premises valuation
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Comparison of bagging, boosting and stacking ensembles applied to real estate appraisal
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Empirical comparison of bagging ensembles created using weak learners for a regression problem
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Fuzzy classification using the data envelopment analysis
Knowledge-Based Systems
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
An efficient multi-objective evolutionary fuzzy system for regression problems
International Journal of Approximate Reasoning
Evaluating the performance of a Bayesian Artificial Immune System for designing fuzzy rule bases
International Journal of Hybrid Intelligent Systems
| Hi-index | 0.00 |
In [14] we proposed a scheme to generate fuzzy rule-based multiclassification systems by means of bagging, mutual information-based feature selection, and a multicriteria genetic algorithm for static component classifier selection guided by the ensemble training error. In the current contribution we extend the latter component by making use of the bagging approach's capability to evaluate the accuracy of the classifier ensemble using the out-of-bag estimates. An exhaustive study is developed on the potential of the two multicriteria genetic algorithms respectively considering the classical training error and the out-of-bag error fitness functions to design a final multiclassifier with an appropriate accuracy-complexity trade-off. Several parameter settings for the global approach are tested when applied to nine popular UCI datasets with different dimensionality.