Machine Learning
High-order contrasts for independent component analysis
Neural Computation
Machine Learning
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Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
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Neural Computation
Combining forecasts with blind signal separation methods in electric load prediction framework
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Smooth component analysis as ensemble method for prediction improvement
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Prediction improvement via smooth component analysis and neural network mixing
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
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In this paper we present the theoretical background for destructive component identification in ensemble method via multivariate decompositions. The identification method is based on second order statistics and it is addressed for predictive models scored by MSE criterion. The validity of the concept is confirmed by simulation study based on Friedman benchmark function.