Pattern recognition: human and mechanical
Pattern recognition: human and mechanical
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Neural fuzzy systems: a neuro-fuzzy synergism to intelligent systems
Predicting a chaotic time series using a fuzzy neural network
Information Sciences: an International Journal
Statistical Pattern Recognition: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
An Accelerated Genetic Algorithm
Applied Intelligence
A perspective view and survey of meta-learning
Artificial Intelligence Review
Advances in Metaheuristics for Hard Optimization (Natural Computing Series)
Advances in Metaheuristics for Hard Optimization (Natural Computing Series)
Expert Systems with Applications: An International Journal
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Tuning of a neuro-fuzzy controller by genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
MAGMA: a multiagent architecture for metaheuristics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetically optimized fuzzy decision trees
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Tuning of the structure and parameters of a neural network using an improved genetic algorithm
IEEE Transactions on Neural Networks
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The existence of many pattern recognition systems (PRSs) and their relative merits and drawbacks highlights the need for a metalearning framework that can find the best PRS method for a given task. To address this issue, a hyperparameter evolutionary optimization (HPEO) framework was previously devised, initially using a genetic algorithm to tune external PRS parameters in a modular fashion, decoupled from its internal components. To further improve the effectiveness of HPEO and improve the diversity of the hyperparameter solutions found, this paper presents an extension that realizes cross-generation learning with an adaptive history network (AHN), which promotes exploring new regions in the search space while avoiding regions that have been searched extensively. The proposed approach, termed HPEO-AHN, is particularly suitable for tuning powerful but complex PRSs such as neuro-fuzzy systems (NFS). Preliminary experiments with two state-of-the-art NFSs optimized using the new approach have shown encouraging results.