Uncertain data decision tree classification algorithm
Chong Wang · Journal of Computer Applications · 2009
Classic decision tree algorithm is unfit to cope with uncertain data pervaded at both the construction and classification phase. In order to overcome these limitations,D-S decision tree classification algorithm was proposed. This algorithm extended the decision tree technique to an uncertain environment. To avoid the combinatorial explosion that would result from tree construction phase,uncertainty measure operator and aggregation combination operator were introduced. This D-S decision tree is a new classification method applied to uncertain data and shows good performance and can efficiently avoid combinatorial explosion.