Machine Learning for the Detection of Oil Spills in Satellite Radar Images
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition
Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition
Data Mining and Knowledge Discovery
Increasing sensitivity of preterm birth by changing rule strengths
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
Editorial: special issue on learning from imbalanced data sets
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Mining with rarity: a unifying framework
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
A study of the behavior of several methods for balancing machine learning training data
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Minority report in fraud detection: classification of skewed data
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Biostatistical Analysis (5th Edition)
Biostatistical Analysis (5th Edition)
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Cost-sensitive boosting for classification of imbalanced data
Pattern Recognition
The class imbalance problem: A systematic study
Intelligent Data Analysis
An Evaluation of the Robustness of MTS for Imbalanced Data
IEEE Transactions on Knowledge and Data Engineering
Fuzzy classifier identification using decision tree and multiobjective evolutionary algorithms
International Journal of Approximate Reasoning
Evolutionary rule-based systems for imbalanced data sets
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
SMOTE: synthetic minority over-sampling technique
Journal of Artificial Intelligence Research
Neighbor-weighted K-nearest neighbor for unbalanced text corpus
Expert Systems with Applications: An International Journal
A proposal on reasoning methods in fuzzy rule-based classification systems
International Journal of Approximate Reasoning
Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study
IEEE Transactions on Evolutionary Computation
Effect of rule weights in fuzzy rule-based classification systems
IEEE Transactions on Fuzzy Systems
Linguistic modeling by hierarchical systems of linguistic rules
IEEE Transactions on Fuzzy Systems
Rule Weight Specification in Fuzzy Rule-Based Classification Systems
IEEE Transactions on Fuzzy Systems
A hybrid coevolutionary algorithm for designing fuzzy classifiers
Information Sciences: an International Journal
A Preliminar Analysis of CO2RBFN in Imbalanced Problems
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Fuzzy qualitative trigonometry
International Journal of Approximate Reasoning
Information Sciences: an International Journal
FSVM-CIL: fuzzy support vector machines for class imbalance learning
IEEE Transactions on Fuzzy Systems - Special section on computing with words
International Journal of Approximate Reasoning
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets
Pattern Recognition Letters
Decision making with imprecise parameters
International Journal of Approximate Reasoning
Diagnosis of dyslexia with low quality data with genetic fuzzy systems
International Journal of Approximate Reasoning
Mining fuzzy rules using an Artificial Immune System with fuzzy partition learning
Applied Soft Computing
Linguistic cost-sensitive learning of genetic fuzzy classifiers for imprecise data
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
A new weighted rough set framework based classification for Egyptian NeoNatal Jaundice
Applied Soft Computing
Expert Systems with Applications: An International Journal
Class distribution estimation based on the Hellinger distance
Information Sciences: an International Journal
Fuzzy machine learning and data mininga
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
A genetic design of linguistic terms for fuzzy rule based classifiers
International Journal of Approximate Reasoning
A hierarchical approach to multi-class fuzzy classifiers
Expert Systems with Applications: An International Journal
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In many real application areas, the data used are highly skewed and the number of instances for some classes are much higher than that of the other classes. Solving a classification task using such an imbalanced data-set is difficult due to the bias of the training towards the majority classes. The aim of this paper is to improve the performance of fuzzy rule based classification systems on imbalanced domains, increasing the granularity of the fuzzy partitions on the boundary areas between the classes, in order to obtain a better separability. We propose the use of a hierarchical fuzzy rule based classification system, which is based on the refinement of a simple linguistic fuzzy model by means of the extension of the structure of the knowledge base in a hierarchical way and the use of a genetic rule selection process in order to get a compact and accurate model. The good performance of this approach is shown through an extensive experimental study carried out over a large collection of imbalanced data-sets.