We propose a generic framework that uses utility in decision making to drive the data mining process. We use concepts from meta-learning and build on earlier work by Elovici and B...
In this paper we propose an original approach to apply data mining algorithms, namely decision tree-based methods, taking into account not only the size of processed databases but ...
We describe an efficient implementation (MRDTL-2) of the Multi-relational decision tree learning (MRDTL) algorithm [23] which in turn was based on a proposal by Knobbe et al. [19] ...
- This short paper compares the performance of three popular decision tree algorithms: C4.5, C5.0, and WEKA's J48. These decision tree algorithms are all related in that C5.0 ...
Samuel Moore, Daniel D'Addario, James Kurinskas, G...
1 In this paper, we propose the use of data mining algorithms to create a macroblock partition mode decision algorithm for inter-frame prediction, to be used as part of a high-effi...