Modelling for Prediction vs. Modelling for Understanding: Commentary on Musso et al. (2013)
Cites background from "Modelling for Prediction vs. Modell..."
... observed that the basic problems of communicating how they reach their conclusions in meaningful terms has yet to be solved....
Cites background or methods or result from "Modelling for Prediction vs. Modell..."
...Edelsbrunner and Schneider (2013) in their commentary on Musso, Kyndt, Cascallar and Dochy (2013) argue that artificial neural networks (ANNs) should only be used as exploratory modelling techniques, in spite of being powerful statistical modelling tools with demonstrated ability to improve…...
...The reasons Edelsbrunner and Schneider (2013) argue for their rather strong position are centred on two main arguments: (a) that the output from ANNs cannot be fully translated into a meaningful set of rules because of a lack of accessibility to the input-output relationships, and (b) that there is…...
...Therefore, contrary to what has been pointed out by Edelsbrunner and Schneider (2013) and quoted by Golino and Gomes (2014), the ANN approach offers the potential to examine the complex relationships amongst its components....
...Now it 69 | F L R expressed in Edelsbrunner & Schneider (2013)....
...The second main argument regarding problems associated with the ANN methodology, as claimed by Edelsbrunner and Schneider (2013), has to do with the lack of some statistical parameters in ANNs....
"Modelling for Prediction vs. Modell..." refers background or methods in this paper
...While one can assess how well an ANN works, it is difficult to comprehensively explain why it performs well or not (Scarborough & Somers, 2006)....
...First, the construction of ANN models such as those used by Musso et al. is highly explorative apart from choosing relevant input and output variables (Günther, Pigeot, &Bammann, 2012; Scarborough & Somers, 2006)....