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» A Genetic Algorithm for Clustering on Very Large Data Sets
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BMCBI
2010
121views more  BMCBI 2010»
13 years 6 months ago
A grammar-based distance metric enables fast and accurate clustering of large sets of 16S sequences
Background: We propose a sequence clustering algorithm and compare the partition quality and execution time of the proposed algorithm with those of a popular existing algorithm. T...
David J. Russell, Samuel F. Way, Andrew K. Benson,...
JDCTA
2010
152views more  JDCTA 2010»
13 years 3 months ago
Spatial Clustering Algorithm Based on Hierarchical-Partition Tree
In spatial clustering, the scale of spatial data is usually very large. Spatial clustering algorithms need high performance, good scalability, and are able to deal with noise and ...
Zhongzhi Li, Xuegang Wang
ISBRA
2007
Springer
14 years 2 months ago
Clustering Algorithms Optimizer: A Framework for Large Datasets
Clustering algorithms are employed in many bioinformatics tasks, including categorization of protein sequences and analysis of gene-expression data. Although these algorithms are r...
Roy Varshavsky, David Horn, Michal Linial
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
14 years 7 days ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Genetic weighted k-means algorithm for clustering large-scale gene expression data
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Fang-Xiang Wu