Robust regression and outlier detection
Robust regression and outlier detection
Multilayer feedforward networks are universal approximators
Neural Networks
Neural network design
TAO-robust backpropagation learning algorithm
Neural Networks
Robust error measure for supervised neural network learning with outliers
IEEE Transactions on Neural Networks
The annealing robust backpropagation (ARBP) learning algorithm
IEEE Transactions on Neural Networks
Robust MCD-Based Backpropagation Learning Algorithm
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
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Training data sets containing outliers are often a problem for supervised neural networks learning algorithms. They may not always come up with acceptable performance and build very inaccurate models. In this paper new, robust to outliers, learning algorithm based on the Least Trimmed Squares (LTS) estimator is proposed. The LTS learning algorithm is simultaneously the first robust learning algorithm that takes into account not only gross errors but also leverage data points. Results of simulations of networks trained with the new algorithm are presented and the robustness against outliers is demonstrated.