C4.5: programs for machine learning
C4.5: programs for machine learning
Artificial Intelligence
Machine Learning
ECSQARU '01 Proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Classiying Scenarios Using Belief Decision Trees
DS '00 Proceedings of the Third International Conference on Discovery Science
International Journal of Intelligent Systems in Accounting and Finance Management
Hi-index | 0.00 |
Decision trees are considered as an efficient technique to express classification knowledge and to use it. However, their most standard algorithms do not deal with uncertainty, especially the cognitive one. In this paper, we develop a method to adapt the decision tree technique to the case where the object's classes are not exactly known, and where the uncertainty about the class' value is represented by a belief function. The adaptation concerns both the construction of the tree and its use to classify new objects characterized by uncertain attribute values.