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ICPP
2000
IEEE
15 years 4 months ago
A Scalable Parallel Subspace Clustering Algorithm for Massive Data Sets
Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Harsha S. Nagesh, Sanjay Goil, Alok N. Choudhary
BMCBI
2010
151views more  BMCBI 2010»
14 years 12 months ago
Misty Mountain clustering: application to fast unsupervised flow cytometry gating
Background: There are many important clustering questions in computational biology for which no satisfactory method exists. Automated clustering algorithms, when applied to large,...
István P. Sugár, Stuart C. Sealfon
PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 3 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...
BMCBI
2004
158views more  BMCBI 2004»
14 years 11 months ago
Incremental genetic K-means algorithm and its application in gene expression data analysis
Background: In recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms suc...
Yi Lu, Shiyong Lu, Farshad Fotouhi, Youping Deng, ...
PPSN
2004
Springer
15 years 5 months ago
Constrained Evolutionary Optimization by Approximate Ranking and Surrogate Models
Abstract. The paper describes an evolutionary algorithm for the general nonlinear programming problem using a surrogate model. Surrogate models are used in optimization when model ...
Thomas Philip Runarsson