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ECSQARU
2005
Springer
14 years 2 months 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
ICDM
2010
IEEE
125views Data Mining» more  ICDM 2010»
13 years 6 months ago
Evolving Ensemble-Clustering to a Feedback-Driven Process
Abstract--Data clustering is a highly used knowledge extraction technique and is applied in more and more application domains. Over the last years, a lot of algorithms have been pr...
Martin Hahmann, Dirk Habich, Wolfgang Lehner
ISPASS
2003
IEEE
14 years 2 months ago
Performance study of a cluster runtime system for dynamic interactive stream-oriented applications
Emerging application domains such as interactive vision, animation, and multimedia collaboration display dynamic scalable parallelism, and high computational requirements, making ...
Arnab Paul, Nissim Harel, Sameer Adhikari, Bikash ...
BMCBI
2006
153views more  BMCBI 2006»
13 years 8 months ago
Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive
Background: Recent advances in genome technologies have provided an excellent opportunity to determine the complete biological characteristics of neoplastic tissues, resulting in ...
Hiro Takahashi, Takeshi Nemoto, Teruhiko Yoshida, ...
AUSDM
2008
Springer
211views Data Mining» more  AUSDM 2008»
13 years 10 months ago
LBR-Meta: An Efficient Algorithm for Lazy Bayesian Rules
LBR is a highly accurate classification algorithm, which lazily constructs a single Bayesian rule for each test instance at classification time. However, its computational complex...
Zhipeng Xie