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» Evaluating algorithms that learn from data streams
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BMCBI
2008
117views more  BMCBI 2008»
15 years 7 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...
PAKDD
2010
ACM
208views Data Mining» more  PAKDD 2010»
15 years 8 months ago
Efficient Pattern Mining of Uncertain Data with Sampling
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
Toon Calders, Calin Garboni, Bart Goethals
BMCBI
2010
133views more  BMCBI 2010»
15 years 7 months ago
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Lance E. Palmer, Mathäus Dejori, Randall A. B...
ACL
2009
15 years 4 months ago
Learning with Annotation Noise
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
Eyal Beigman, Beata Beigman Klebanov
PAISI
2009
Springer
16 years 1 months ago
Discovering Compatible Top-K Theme Patterns from Text Based on Users' Preferences
Discovering a representative set of theme patterns from a large amount of text for interpreting their meaning has always been concerned by researches of both data mining and inform...
Yongxin Tong, Shilong Ma, Dan Yu, Yuanyuan Zhang, ...