Abstract
The paper deals with an application of the theory of optimum experimental design to the problem of selecting the data set for developing neural models. Another objective is to show that neural network trained with the samples obtained according to D-optimum design is endowed with less parameters uncertainty what allows to obtain more reliable tool for modelling purposes. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Prȩtki, P., & Witczak, M. (2005). Developing measurement selection strategy for neural network models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3697 LNCS, pp. 79–84). https://doi.org/10.1007/11550907_13
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