Rotation Forest is a recently proposed method for building classifier ensembles using independently trained decision trees. It was found to be more accurate than bagging, AdaBoost...
In this paper we propose a new data structure, called shared automata, for representing deterministic finite automata (DFA). Shared automata admit a strong canonical form for DFA ...
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simple...
Successful application of model-driven engineering approaches requires interchanging a lot of relevant data among the tool ecosystem employed by an engineering team (e.g., requirem...
Data provenance is essential in applications such as scientific computing, curated databases, and data warehouses. Several systems have been developed that provide provenance fun...