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1998

Using Decision Trees for Agent Modeling: Improving Prediction Performance

8 years 5 months ago
Using Decision Trees for Agent Modeling: Improving Prediction Performance
A modeling system may be required to predict an agent’s future actions under constraints of inadequate or contradictory relevant historical evidence. This can result in low prediction accuracy, or otherwise, low prediction rates, leaving a set of cases for which no predictions are made. A previous study that explored techniques for improving prediction rates in the context of modeling students’ subtraction skills using Feature Based Modeling showed a tradeoff between prediction rate and predication accuracy. This paper presents research that aims to improve prediction rates without affecting prediction accuracy. The FBM-C4.5 agent modeling system was used in this research. However, the techniques explored are applicable to any Feature Based Modeling system, and the most effective technique developed is applicable to most agent modeling systems. The default FBM-C4.5 system models agents’ competencies with a set of decision trees, trained on all historical data. Each tree predicts ...
Bark Cheung Chiu, Geoffrey I. Webb
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 1998
Where UMUAI
Authors Bark Cheung Chiu, Geoffrey I. Webb
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