1 Erratum to: Qual Quant DOI 10.1007/s11135-016-0329-y
In the original publication of the article, the Italian quotes starts from “La tecnica” and ends with “della conoscenza” under the heading “Methods” which has been included by mistake should be removed and replaced with the following English translation “The auto-encoder technology allows the optimization of the learning process. The purpose of this type of learning (autoencoder) is to measure the ability to understand the logic of a dataset. It is, in other words, a sort of “calibration mechanism” of knowledge”.
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The online version of the original article can be found under doi:10.1007/s11135-016-0329-y.
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Buscema, P.M., Maurelli, G., Mennini, F.S. et al. Erratum to: Artificial neural networks and their potentialities in analyzing budget health data: an application for Italy of what-if theory. Qual Quant 51, 1277–1278 (2017). https://doi.org/10.1007/s11135-016-0359-5
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DOI: https://doi.org/10.1007/s11135-016-0359-5