Learning and Evolution by Minimization of Mutual Information
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Learning-Data Selection Mechanism through Neural Networks Ensemble
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
A Preliminary Study on Negative Correlation Learning via Correlation-Corrected Data (NCCD)
Neural Processing Letters
Evolving Neural Network Ensembles by Minimization of Mutual Information
International Journal of Hybrid Intelligent Systems
Heuristic speciation for evolving neural network ensemble
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Expert Systems with Applications: An International Journal
Increasing classification efficiency with multiple mirror classifiers
Expert Systems with Applications: An International Journal
A Balanced Ensemble Learning with Adaptive Error Functions
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Negative correlation in incremental learning
Natural Computing: an international journal
The Research of Negative Correlation Learning Based on Artificial Neural Network
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Balanced Learning for Ensembles with Small Neural Networks
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
The Research of Artificial Neural Network on Negative Correlation Learning
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Profiling of Mass Spectrometry Data for Ovarian Cancer Detection Using Negative Correlation Learning
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Neural network ensemble training by sequential interaction
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Evolving, training and designing neural network ensembles
INES'10 Proceedings of the 14th international conference on Intelligent engineering systems
Negative correlation learning of neuro-fuzzy system ensembles
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Hybrid ensemble approach for classification
Applied Intelligence
A principled evaluation of ensembles of learning machines for software effort estimation
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part III
Aggregating regressive estimators: gradient-based neural network ensemble
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Negatively correlated neural network ensemble with multi-population particle swarm optimization
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
How to stop the evolutionary process in evolving neural network ensembles
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Generate different neural networks by negative correlation learning
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Using Bagging and Cross-Validation to improve ensembles based on penalty terms
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
The build of n-Bits Binary Coding ICBP Ensemble System
Neurocomputing
Incorporation of a Regularization Term to Control Negative Correlation in Mixture of Experts
Neural Processing Letters
Minimal correlation classification
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VI
Exploiting unlabeled data to enhance ensemble diversity
Data Mining and Knowledge Discovery
Software effort estimation as a multiobjective learning problem
ACM Transactions on Software Engineering and Methodology (TOSEM) - Testing, debugging, and error handling, formal methods, lifecycle concerns, evolution and maintenance
Transition Learning by Negative Correlation Learning
Proceedings of the Second International Conference on Innovative Computing and Cloud Computing
Using Bayesian networks for selecting classifiers in GP ensembles
Information Sciences: an International Journal
Neural network modeling of vector multivariable functions in ill-posed approximation problems
Journal of Computer and Systems Sciences International
Boosted Pre-loaded Mixture of Experts for low-resolution face recognition
International Journal of Hybrid Intelligent Systems
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This paper presents a new cooperative ensemble learning system (CELS) for designing neural network ensembles. The idea behind CELS is to encourage different individual networks in an ensemble to learn different parts or aspects of a training data so that the ensemble can learn the whole training data better. In CELS, the individual networks are trained simultaneously rather than independently or sequentially. This provides an opportunity for the individual networks to interact with each other and to specialize. CELS can create negatively correlated neural networks using a correlation penalty term in the error function to encourage such specialization. This paper analyzes CELS in terms of bias-variance-covariance tradeoff. CELS has also been tested on the Mackey-Glass time series prediction problem and the Australian credit card assessment problem. The experimental results show that CELS can produce neural network ensembles with good generalization ability