Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Transformation Invariance in Pattern Recognition-Tangent Distance and Tangent Propagation
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Fast learning process of multilayer neural networks using recursiveleast squares method
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
A constructive approach for finding arbitrary roots of polynomials by neural networks
IEEE Transactions on Neural Networks
Zeroing polynomials using modified constrained neural network approach
IEEE Transactions on Neural Networks
An improved algorithm for neural network classification of imbalanced training sets
IEEE Transactions on Neural Networks
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets
Pattern Recognition Letters
An improved harmony search algorithms based on particle swarm optimizer
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
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In this paper, a novel modular neural network is proposed to solve multi-class problems with imbalanced training sets. The proposed model can transform an imbalanced classification problem into a set of symmetrical two-class problems, each of which is solved by single neural network with a simple structure. The results of all neural networks are then combined by averaging or GA method to form a final classification decision. The experimental results show that the proposed method reduces the time consumption for training and improves the classification performance.