In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing ...
We study how several collective operations like broadcast, reduction, scan, etc. can be composed efficiently in complex parallel programs. Our specific contributions are: (1) a fo...
Sergei Gorlatch, Christoph Wedler, Christian Lenga...
Associative classification is a novel and powerful method originating from association rule mining. In the previous studies, a relatively small number of high-quality association...
To avoid the loss of semantic information due to the partition of quantitative values, this paper proposes a novel algorithm, called MPSQAR, to handle the quantitative association ...
Chunqiu Zeng, Jie Zuo, Chuan Li, Kaikuo Xu, Shengq...
Abstract. We describe EDRL-MD, an evolutionary algorithm-based system, for learning decision rules from databases. The main novelty of our approach lies in dealing with continuous ...