We present an improvement to Harvey and Ginsberg's limited discrepancy search algorithm, which eliminates much of the redundancy in the original, by generating each path from...
Model trees—decision trees with linear models at the leaf nodes—have recently emerged as an accurate method for numeric prediction that produces understandable models. However,...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
In this paper we introduce the evolution tree - a software life-cycle model that describes software development as the continuous evolution of a software product. That is, we view...
Trees provide a suited structural representation to deal with complex tasks such as web information extraction, RNA secondary structure prediction, or conversion of tree structured...