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”.
Buscema, P.m., Maurelli, G., Mennini, F.s., Gitto, L., Russo, S., Ruggeri, M., et al. (2017). Erratum to: Artificial neural networks and their potentialities in analyzing budget health data: an application for Italy of what-if theory. QUALITY & QUANTITY, 51(3), 1277-1278 [10.1007/s11135-016-0359-5].
Erratum to: Artificial neural networks and their potentialities in analyzing budget health data: an application for Italy of what-if theory
Mennini F. S.
Methodology
;Gitto L.Membro del Collaboration Group
;
2017-01-01
Abstract
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”.| File | Dimensione | Formato | |
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