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» Mining the optimal class association rule set
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TKDE
2002
133views more  TKDE 2002»
14 years 11 months ago
Binary Rule Generation via Hamming Clustering
The generation of a set of rules underlying a classification problem is performed by applying a new algorithm, called Hamming Clustering (HC). It reconstructs the and-or expressio...
Marco Muselli, Diego Liberati
GECCO
2006
Springer
214views Optimization» more  GECCO 2006»
15 years 3 months ago
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
TIT
2008
90views more  TIT 2008»
14 years 11 months ago
On Optimal Quantization Rules for Some Problems in Sequential Decentralized Detection
We consider the design of systems for sequential decentralized detection, a problem that entails several interdependent choices: the choice of a stopping rule (specifying the samp...
XuanLong Nguyen, Martin J. Wainwright, Michael I. ...
GECCO
2003
Springer
15 years 5 months ago
Mining Comprehensible Clustering Rules with an Evolutionary Algorithm
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...
PKDD
2000
Springer
159views Data Mining» more  PKDD 2000»
15 years 3 months ago
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
Abstract. This paper proposes a novel approach named AGM to eciently mine the association rules among the frequently appearing substructures in a given graph data set. A graph tran...
Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda