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» Model order selection for bio-molecular data clustering
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DASFAA
2007
IEEE
178views Database» more  DASFAA 2007»
15 years 6 months ago
ClusterSheddy : Load Shedding Using Moving Clusters over Spatio-temporal Data Streams
Abstract. Moving object environments are characterized by large numbers of objects continuously sending location updates. At times, data arrival rates may spike up, causing the loa...
Rimma V. Nehme, Elke A. Rundensteiner
IDA
2002
Springer
14 years 11 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
BMCBI
2010
153views more  BMCBI 2010»
14 years 11 months ago
Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering
Background: Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or su...
Eva Freyhult, Mattias Landfors, Jenny Önskog,...
ICASSP
2008
IEEE
15 years 6 months ago
Optimizing the acoustic modeling from an unbalanced bi-lingual corpus
Phoneme set clustering of accurate modeling is important in the task of multilingual speech recognition, especially when each of the available language training corpora is mismatc...
Dau-cheng Lyu, Ren-yuan Lyu
ICDE
2005
IEEE
132views Database» more  ICDE 2005»
15 years 5 months ago
CLICKS: Mining Subspace Clusters in Categorical Data via K-partite Maximal Cliques
We present a novel algorithm called CLICKS, that finds clusters in categorical datasets based on a search for kpartite maximal cliques. Unlike previous methods, CLICKS mines subs...
Mohammed Javeed Zaki, Markus Peters