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GI
1998
Springer
14 years 18 days ago
Self-Organizing Data Mining
"KnowledgeMiner" was designed to support the knowledge extraction process on a highly automated level. Implemented are 3 different GMDH-type self-organizing modeling algo...
Frank Lemke, Johann-Adolf Müller
GECCO
2010
Springer
211views Optimization» more  GECCO 2010»
13 years 9 months ago
Investigating EA solutions for approximate KKT conditions in smooth problems
Evolutionary algorithms (EAs) are increasingly being applied to solve real-parameter optimization problems due to their flexibility in handling complexities such as non-convexity,...
Rupesh Tulshyan, Ramnik Arora, Kalyanmoy Deb, Joyd...
BMCBI
2010
110views more  BMCBI 2010»
13 years 8 months ago
Discovering local patterns of co - evolution: computational aspects and biological examples
Background: Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn abo...
Tamir Tuller, Yifat Felder, Martin Kupiec
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
14 years 28 days ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...
PAKDD
2005
ACM
146views Data Mining» more  PAKDD 2005»
14 years 1 months ago
An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection
Abstract. The data stream model of computation is often used for analyzing huge volumes of continuously arriving data. In this paper, we present a novel algorithm called DUCstream ...
Jing Gao, Jianzhong Li, Zhaogong Zhang, Pang-Ning ...