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ICML
2009
IEEE
14 years 4 months ago
Rule learning with monotonicity constraints
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 ...
Wojciech Kotlowski, Roman Slowinski
IPPS
1999
IEEE
14 years 2 months ago
Optimization Rules for Programming with Collective Operations
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...
SEMCO
2008
IEEE
14 years 4 months ago
Text Categorization Based on Boosting Association Rules
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...
Yongwook Yoon, Gary Geunbae Lee
ADMA
2008
Springer
152views Data Mining» more  ADMA 2008»
14 years 4 months ago
MPSQAR: Mining Quantitative Association Rules Preserving Semantics
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...
PKDD
1999
Springer
103views Data Mining» more  PKDD 1999»
14 years 2 months ago
An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction
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 ...
Wojciech Kwedlo, Marek Kretowski