Radial basis functions for multivariable interpolation: a review
Algorithms for approximation
Neural network implementation of fuzzy logic
Fuzzy Sets and Systems
A review and comparison of six reasoning methods
Fuzzy Sets and Systems
FCMAC: a fuzzified cerebellar model articulation controller with self-organizing capacity
Automatica (Journal of IFAC)
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Machine Learning - Special issue on learning with probabilistic representations
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
An experiment in linguistic synthesis with a fuzzy logic controller
International Journal of Human-Computer Studies - Special issue: 1969-1999, the 30th anniversary
Foundations of Neuro-Fuzzy Systems
Foundations of Neuro-Fuzzy Systems
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
An introduction to ROC analysis
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Cognitive Architectures: Where do we go from here?
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Gene selection from microarray data for cancer classification-a machine learning approach
Computational Biology and Chemistry
A novel dual neuro-fuzzy system approach for large-scale knowledge consolidation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Knowledge Consolidation and Inference in the Integrated Neuro-Cognitive Architecture
IEEE Intelligent Systems
Evolving fuzzy neural networks for supervised/unsupervised onlineknowledge-based learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Robust and fast learning for fuzzy cerebellar model articulation controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
FCMAC-BYY: Fuzzy CMAC Using Bayesian Ying–Yang Learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An ART-based fuzzy adaptive learning control network
IEEE Transactions on Fuzzy Systems
Evolving Fuzzy-Rule-Based Classifiers From Data Streams
IEEE Transactions on Fuzzy Systems
Reinforcement structure/parameter learning for neural-network-based fuzzy logic control systems
IEEE Transactions on Fuzzy Systems
On the entropy of continuous probability distributions (Corresp.)
IEEE Transactions on Information Theory
A neuro-fuzzy scheme for simultaneous feature selection and fuzzy rule-based classification
IEEE Transactions on Neural Networks
FCMAC-Yager: A Novel Yager-Inference-Scheme-Based Fuzzy CMAC
IEEE Transactions on Neural Networks
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Neuro-fuzzy system (NFS) and especially localized NFS are powerful rule-based methods for knowledge extraction, capable of inducing salient knowledge structures from data automatically. Contemporary localized NFSs, however, often demand large features and rules to accurately describe the overall domain data, thus degrading their interpretability and generalization traits. In light of these issues, a new localized NFS termed the Reduced Fuzzy Cerebellar Model Articulation Controller (RFCMAC) is proposed that models the two-stage neural development of cortical memories in the brain to construct and reduce the human's memory structure. This idea is realized in both label generation and rule generation phases of the RFCMAC learning process to derive a compact and representative rule base structure, prior to an iterative parameter tuning phase. The incorporation of reduction mechanisms provides RFCMAC with several benefits over classical localized NFSs, including discovery of highly concise and intuitive rules, satisfactory generalization performances, and enhanced system scalability. A series of experiments on nonlinear regression, water plant monitoring, and leukemia diagnosis tasks have demonstrated the efficacy of the proposed system as a novel knowledge extraction tool.