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CEC
2007
IEEE
14 years 1 months ago
A co-evolutionary framework for regulatory motif discovery
Abstract— In previous work, we have shown how an evolutionary algorithm with a clustered population can be used to concurrently discover multiple regulatory motifs present within...
Michael A. Lones, Andy M. Tyrrell
CORR
2010
Springer
74views Education» more  CORR 2010»
13 years 7 months ago
Significance of Classification Techniques in Prediction of Learning Disabilities
The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age chil...
Julie M. David, Kannan Balakrishnan
ICTAI
2003
IEEE
14 years 25 days ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
14 years 1 months ago
Towards clustering with XCS
This paper presents a novel approach to clustering using an accuracy-based Learning Classifier System. Our approach achieves this by exploiting the generalization mechanisms inher...
Kreangsak Tamee, Larry Bull, Ouen Pinngern
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
14 years 8 months ago
A multi-relational approach to spatial classification
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
Richard Frank, Martin Ester, Arno Knobbe