Pattern classification with compact distribution maps
Computer Vision and Image Understanding
Complexity Measures of Supervised Classification Problems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature subset selection using a new definition of classifiability
Pattern Recognition Letters
On the Nonlinearity of Pattern Classifiers
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Multiresolution Estimates of Classification Complexity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification and Modeling with Linguistic Information Granules: Advanced Approaches to Linguistic Data Mining (Advanced Information Processing)
Data complexity assessment in undersampled classification of high-dimensional biomedical data
Pattern Recognition Letters
Data Complexity in Pattern Recognition (Advanced Information and Knowledge Processing)
Data Complexity in Pattern Recognition (Advanced Information and Knowledge Processing)
Preface: Special Issue on Genetic Fuzzy Systems and the Interpretability--Accuracy Trade-off
International Journal of Approximate Reasoning
Introduction: Genetic fuzzy systems: Introduction
International Journal of Intelligent Systems
An analysis of how training data complexity affects the nearest neighbor classifiers
Pattern Analysis & Applications
Pattern Classifier Design by Linear Programming
IEEE Transactions on Computers
Special issue on “Genetic Fuzzy Systems: Recent Developments and Future Directions”
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Genetic Fuzzy Systems: Recent Developments and Future Directions; Guest editors: Jorge Casillas, Brian Carse
A proposal on reasoning methods in fuzzy rule-based classification systems
International Journal of Approximate Reasoning
Fuzzy Classifier Design
Data characterization for effective prototype selection
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Domain of competence of XCS classifier system in complexity measurement space
IEEE Transactions on Evolutionary Computation
Hybridization of fuzzy GBML approaches for pattern classification problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Guest Editorial Genetic Fuzzy Systems: What's Next? An Introduction to the Special Section
IEEE Transactions on Fuzzy Systems
Classifiability-based omnivariate decision trees
IEEE Transactions on Neural Networks
Information Sciences: an International Journal
International Journal of Approximate Reasoning
Information Sciences: an International Journal
Analysing the low quality of the data in lighting control systems
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Linear separability and classification complexity
Expert Systems with Applications: An International Journal
Comparison of fuzzy functions for low quality data GAP algorithms
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
Intelligent Information Retrieval Using Fuzzy Association Rule Classifier
International Journal of Intelligent Information Technologies
Domains of competence of the semi-naive Bayesian network classifiers
Information Sciences: an International Journal
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The analysis of data complexity is a proper framework to characterize the tackled classification problem and to identify domains of competence of classifiers. As a practical outcome of this framework, the proposed data complexity measures may facilitate the choice of a classifier for a given problem. The aim of this paper is to study the behaviour of a fuzzy rule based classification system and its relationship to data complexity. We use as a case of study the fuzzy hybrid genetic based machine learning method presented in [H. Ishibuchi, T. Yamamoto, T. Nakashima, Hybridization of fuzzy GBML approaches for pattern classification problems, IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics 35 (2) (2005) 359-365]. We examine several metrics of data complexity over a wide range of data sets built from real data and try to extract behaviour patterns from the results. We obtain rules which describe both good or bad behaviours of the fuzzy rule based classification system. These rules use values of data complexity metrics in their antecedents, so we try to predict the behaviour of the method from the data set complexity metrics prior to its application. Therefore, we can establish the domains of competence of this fuzzy rule based classification system.