Random Forests for multiclass classification: Random MultiNomial Logit
Expert Systems with Applications: An International Journal
Classifier based text mining for radial basis function
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Technical data mining with evolutionary radial basis function classifiers
Applied Soft Computing
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
EMORBFN: An Evolutionary Multiobjetive Optimization Algorithm for RBFN Design
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Information Sciences: an International Journal
A pilot sampling method for multi-layer perceptrons
ICCOMP'09 Proceedings of the WSEAES 13th international conference on Computers
Performance comparison of RBF networks and MLPs for classification
AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications
The relationship of sample size and accuracy in radial basis function networks
WSEAS Transactions on Computers
An empirical improvement of the accuracy of RBF networks
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Empirical determination of sample sizes for multi-layer perceptrons by simple RBF networks
WSEAS Transactions on Computers
IEEE Transactions on Neural Networks
CO$^2$RBFN for short-term forecasting of the extra virgin olive oil price in the Spanish market
International Journal of Hybrid Intelligent Systems - Hybrid Fuzzy Models
Applying multiobjective RBFNNs optimization and feature selection to a mineral reduction problem
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Evolving an automatic defect classification tool
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Evolutionary Fuzzy ARTMAP Neural Networks and their Applications to Fault Detection and Diagnosis
Neural Processing Letters
So near and yet so far: New insight into properties of some well-known classifier paradigms
Information Sciences: an International Journal
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets
Pattern Recognition Letters
Application of data mining techniques for customer lifetime value parameters: a review
International Journal of Business Information Systems
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Fuzzy ARTMAP and hybrid evolutionary programming for pattern classification
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
The effect of training set size for the performance of neural networks of classification
WSEAS Transactions on Computers
Property of artificial neural networks of classification with respect to training set size
ICS'10 Proceedings of the 14th WSEAS international conference on Systems: part of the 14th WSEAS CSCC multiconference - Volume II
Intrusion detection using neural based hybrid classification methods
Computer Networks: The International Journal of Computer and Telecommunications Networking
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Hybrid artificial neural networks: models, algorithms and data
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Exploiting randomness for feature selection in multinomial logit: a CRM cross-sell application
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Feedback controlled particle swarm optimization and its application in time-series prediction
Expert Systems with Applications: An International Journal
Diversity Guided Evolutionary Programming: A novel approach for continuous optimization
Applied Soft Computing
Accurate Prediction of Coronary Artery Disease Using Reliable Diagnosis System
Journal of Medical Systems
Expert Systems with Applications: An International Journal
Alternative OVA proposals for cooperative competitive RBFN design in classification tasks
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Robust Neuroevolutionary Identification of Nonlinear Nonstationary Objects
Cybernetics and Systems Analysis
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In many data mining applications that address classification problems, feature and model selection are considered as key tasks. That is, appropriate input features of the classifier must be selected from a given (and often large) set of possible features and structure parameters of the classifier must be adapted with respect to these features and a given data set. This paper describes an evolutionary algorithm (EA) that performs feature and model selection simultaneously for radial basis function (RBF) classifiers. In order to reduce the optimization effort, various techniques are integrated that accelerate and improve the EA significantly: hybrid training of RBF networks, lazy evaluation, consideration of soft constraints by means of penalty terms, and temperature-based adaptive control of the EA. The feasibility and the benefits of the approach are demonstrated by means of four data mining problems: intrusion detection in computer networks, biometric signature verification, customer acquisition with direct marketing methods, and optimization of chemical production processes. It is shown that, compared to earlier EA-based RBF optimization techniques, the runtime is reduced by up to 99% while error rates are lowered by up to 86%, depending on the application. The algorithm is independent of specific applications so that many ideas and solutions can be transferred to other classifier paradigms.