Modelling for understanding AND for prediction/classification - the power of neural networks in research
Two articles, Edelsbrunner and, Schneider (2013), and Nokelainen and Silander (2014) comment on Musso, Kyndt, Cascallar, and Dochy (2013). Several relevant issues are raised and some important clarifications are made in response to both commentaries. Predictive systems based on artificial neural net...
Saved in:
Main Authors: | Eduardo Cascallar (Author), Mariel F. Musso (Author), Eva Kyndt (Author), Filip Dochy (Author) |
---|---|
Format: | Book |
Published: |
EARLI,
2015-01-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predicting general academic performance and identifying the differential contribution of participating variables using artificial neural networks
by: Mariel F. Musso, et al.
Published: (2013) -
Turning points during the life of student project teams: A qualitative study
by: Elisabeth Raes, et al.
Published: (2015) -
Group, team, or something in between? Conceptualising and measuring team entitativity
by: Katrien Vangrieken, et al.
Published: (2017) -
Team entitativity and teacher teams in schools: Towards a typology
by: Katrien Vangrieken, et al.
Published: (2013) -
Wind Power Prediction Using Neural Networks with Different Training Models
by: Sana Mohsin Babbar, et al.
Published: (2022)