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ERIC Number: EJ1090838
Record Type: Journal
Publication Date: 2014
Pages: 5
Abstractor: As Provided
ISSN: EISSN-2295-3159
Using New Models to Analyze Complex Regularities of the World: Commentary on Musso et al. (2013)
Nokelainen, Petri; Silander, Tomi
Frontline Learning Research, v2 n1 p78-82 2014
This commentary to the recent article by Musso et al. (2013) discusses issues related to model fitting, comparison of classification accuracy of generative and discriminative models, and two (or more) cultures of data modeling. We start by questioning the extremely high classification accuracy with an empirical data from a complex domain. There is a risk that we model perfect nonsense perfectly. Our second concern is related to the relevance of comparing multilayer perceptron neural networks and linear discriminant analysis classification accuracy indices. We find this problematic, as it is like comparing apples and oranges. It would have been easier to interpret the model and the variable (group) importance's if the authors would have compared MLP to some discriminative classifier, such as group lasso logistic regression. Finally, we conclude our commentary with a discussion about the predictive properties of the adopted data modeling approach.
European Association for Research on Learning and Instruction. Peterseliegang 1, Box 1, 3000 Leuven, Belgium. e-mail:; Web site:
Publication Type: Journal Articles; Reports - Evaluative; Opinion Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A