Title
CONTRIBUTION OF PRIOR KNOWLEDGE TO PROBABILISTIC PREDICTION OF FAMINE
Abstract
The contribution of prior knowledge in prediction of change in food crop prices using ordinary linear regression OLR and Gaussian process GP based on a probabilistic approach in famine predictions was established in this study. Prior information was obtained from previous results and incorporated into a new dataset. For GP, both approaches incorporating weight-space view and function-space view were applied and results compared. The function-space view produced a more suitable model than the weight-space view and OLR. Probabilistic inference showed better famine prediction accuracy than the conventional inference approach. Addition of prior information into the prediction framework improved prediction. It is recommended that in addition to the developed model, further modeling should be carried out to include the effects of variables such as bumper harvest, availability of inexpensive alternative foodstuffs for consumption, imported foodstuffs to remedy famine, effect of neighborhood price, and cross-border trade.
Year
DOI
Venue
2013
10.1080/08839514.2013.848750
Applied Artificial Intelligence
Keywords
DocType
Volume
prior knowledge,famine prediction,function-space view,developed model,conventional inference approach,better famine prediction accuracy,probabilistic prediction,prediction framework improved prediction,prior information,probabilistic approach,weight-space view
Journal
27
Issue
ISSN
Citations 
10
0883-9514
2
PageRank 
References 
Authors
0.37
4
2
Name
Order
Citations
PageRank
Washington Okori162.16
Joseph Obua220.71