Expert Systems with Applications: An International Journal
Improving multiclass pattern recognition with a co-evolutionary RBFNN
Pattern Recognition Letters
International Journal of Business Intelligence and Data Mining
Constructing Classification Rules Based on SVR and Its Derivative Characteristics
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
A New Approach to Division of Attribute Space for SVR Based Classification Rule Extraction
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Feature Selection Based on the Rough Set Theory and Expectation-Maximization Clustering Algorithm
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Development of Design Strategy for RBF Neural Network with the Aid of Context-Based FCM
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Manifold-based learning and synthesis
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Review: Using support vector machines in diagnoses of urological dysfunctions
Expert Systems with Applications: An International Journal
A new approach to symbolic classification rule extraction based on SVM
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Dual-population based coevolutionary algorithm for designing RBFNN with feature selection
Expert Systems with Applications: An International Journal
Energy Supervised Relevance Neural Gas for Feature Ranking
Neural Processing Letters
Simultaneous feature selection and parameters optimization for SVM by immune clonal algorithm
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Training RBF neural networks with PSO and improved subtractive clustering algorithms
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
A simple rule extraction method using a compact RBF neural network
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Effects of feature selection on the identification of students with learning disabilities using ANN
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Dimensionality reduction for evolving RBF networks with particle swarms
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Self-organized locally linear embedding for nonlinear dimensionality reduction
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
A genetic approach to data dimensionality reduction using a special initial population
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
Active mining discriminative gene sets
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
ReinSel: A class-based mechanism for feature selection in ensemble of classifiers
Applied Soft Computing
Novel weighting in single hidden layer feedforward neural networks for data classification
Computers & Mathematics with Applications
Predicting seminal quality with artificial intelligence methods
Expert Systems with Applications: An International Journal
Uncovering overlapping cluster structures via stochastic competitive learning
Information Sciences: an International Journal
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For high dimensional data, if no preprocessing is carried out before inputting patterns to classifiers, the computation required may be too heavy. For example, the number of hidden units of a radial basis function (RBF) neural network can be too large. This is not suitable for some practical applications due to speed and memory constraints. In many cases, some attributes are not relevant to concepts in the data at all. In this paper, we propose a novel separability-correlation measure (SCM) to rank the importance of attributes. According to the attribute ranking results, different attribute subsets are used as inputs to a classifier, such as an RBF neural network. Those attributes that increase the validation error are deemed irrelevant and are deleted. The complexity of the classifier can thus be reduced and its classification performance improved. Computer simulations show that our method for attribute importance ranking leads to smaller attribute subsets with higher accuracies compared with the existing SUD and Relief-F methods. We also propose a modified method for efficient construction of an RBF classifier. In this method we allow for large overlaps between clusters corresponding to the same class label. Our approach significantly reduces the structural complexity of the RBF network and improves the classification performance.