Titlebook: Combining Artificial Neural Nets; Ensemble and Modular Amanda J. C. Sharkey Book 1999 Springer-Verlag London Limited 1999 Ensembl.cognition

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A Comparison of Visual Cue Combination Models, three models of visual cue combination: a weak fusion model, a modified weak fusion model, and a strong fusion model. Their relative strengths and weaknesses are evaluated on the basis of their performances on the tasks of judging the depth and shape of an ellipse. The models differ in the amount o

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Self-Organised Modular Neural Networks for Encoding Data, to illustrate this is encoding high-dimensional data, such as images, where multiple network modules implement a factorial encoder, in which the high-dimensional data space is broken up into a number of lowdimensional subspaces, each of which is separately encoded. This type of factorial encoder em

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,Lieferantennähe: SØR Rusche GmbH,enerate the ensemble, the most common approach is through perturbations of the training set and construction of the same algorithm (trees, neural nets, etc.) using the perturbed training sets. But other methods of generating ensembles have also been explored. Combination is achieved by averaging the