The Strength of Weak Learnability
Machine Learning
Original Contribution: Stacked generalization
Neural Networks
Fuzzy Systems as Universal Approximators
IEEE Transactions on Computers
Learning in the presence of concept drift and hidden contexts
Machine Learning
Machine Learning
Mining concept-drifting data streams using ensemble classifiers
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Incremental learning with partial instance memory
Artificial Intelligence
A Theoretical Analysis of Bagging as a Linear Combination of Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Investigation of evolutionary optimization methods of TSK fuzzy model for real estate appraisal
International Journal of Hybrid Intelligent Systems - Recent Advances in Intelligent Paradigms Fusion and Their Applications
Looking for a good fuzzy system interpretability index: An experimental approach
International Journal of Approximate Reasoning
The Impact of Diversity on Online Ensemble Learning in the Presence of Concept Drift
IEEE Transactions on Knowledge and Data Engineering
Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications
Evolving Fuzzy Systems - Methodologies, Advanced Concepts and Applications
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Accuracy updated ensemble for data streams with concept drift
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Empirical comparison of resampling methods using genetic fuzzy systems for a regression problem
IDEAL'11 Proceedings of the 12th international conference on Intelligent data engineering and automated learning
Fuzzy systems with defuzzification are universal approximators
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A two-stage evolutionary process for designing TSK fuzzy rule-basedsystems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An approach to online identification of Takagi-Sugeno fuzzy models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
FLEXFIS: A Robust Incremental Learning Approach for Evolving Takagi–Sugeno Fuzzy Models
IEEE Transactions on Fuzzy Systems
On employing fuzzy modeling algorithms for the valuation of residential premises
Information Sciences: an International Journal
Incremental Learning of Concept Drift in Nonstationary Environments
IEEE Transactions on Neural Networks
An analysis of change trends by predicting from a data stream using genetic fuzzy systems
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
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An approach to apply ensembles of genetic fuzzy systems, built over the chunks of a data stream, to aid in residential premises valuation was proposed. The approach consists in incremental expanding an ensemble by systematically generated models in the course of time. The output of aged component models produced for current data is updated according to a trend function reflecting the changes of premises prices since the moment of individual model generation. An experimental evaluation of the proposed method using real-world data taken from a dynamically changing real estate market revealed its advantage in terms of predictive accuracy.