A Decision-Tree Classifier Hybrid Model of Eager Strategy and Lazy Strategy
Huang Ze · 2005
The eager strategy and lazy strategy have different learning and classification mechanism.On the basis of analyzing regular decision tree classification model adopting eager strategy and lazy decision-tree classification model adopting lazy strategy,we propose a new decision-tree classification model,Semi-LDtree: the decision-tree nodes contain univariate splits as regular decision-trees,but the leaves contain lazy decision-tree classifiers.This classification model retains the good interpretability of decision-tree.The experimental results show this model has the higher classification accuracy and faster speed,especially on the larger databases tested.