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BIODATAMINING
2008
96views more  BIODATAMINING 2008»
15 years 6 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
167
Voted
BMCBI
2007
175views more  BMCBI 2007»
15 years 6 months ago
CLUSS: Clustering of protein sequences based on a new similarity measure
Background: The rapid burgeoning of available protein data makes the use of clustering within families of proteins increasingly important. The challenge is to identify subfamilies...
Abdellali Kelil, Shengrui Wang, Ryszard Brzezinski...
ECSQARU
2005
Springer
16 years 6 days ago
Default Clustering from Sparse Data Sets
Categorization with a very high missing data rate is seldom studied, especially from a non-probabilistic point of view. This paper proposes a new algorithm called default clusterin...
Julien Velcin, Jean-Gabriel Ganascia
IDEAL
2004
Springer
16 years 1 days ago
The Application of K-Medoids and PAM to the Clustering of Rules
Abstract. Earlier research has resulted in the production of an ‘allrules’ algorithm for data-mining that produces all conjunctive rules of above given confidence and coverage...
Alan P. Reynolds, Graeme Richards, Victor J. Raywa...
FOCS
2000
IEEE
15 years 11 months ago
Clustering Data Streams
The data stream model has recently attracted attention for its applicability to numerous types of data, including telephone records, web documents and clickstreams. For analysis o...
Sudipto Guha, Nina Mishra, Rajeev Motwani, Liadan ...