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» Discovering Case Knowledge Using Data Mining
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KDD
2009
ACM
140views Data Mining» more  KDD 2009»
14 years 8 months ago
Improving clustering stability with combinatorial MRFs
: ? Improving Clustering Stability with Combinatorial MRFs Bekkerman, Ron; Scholz, Martin; Viswanathan, Krishnamurthy HP Laboratories HPL-2009-46 Clustering stability, combinatoria...
Ron Bekkerman, Martin Scholz, Krishnamurthy Viswan...
PROMISE
2010
13 years 2 months ago
Case-based reasoning vs parametric models for software quality optimization
Background: There are many data mining methods but few comparisons between them. For example, there are at least two ways to build quality optimizers, programs that find project o...
Adam Brady, Tim Menzies
CIKM
2010
Springer
13 years 5 months ago
Regularization and feature selection for networked features
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Hongliang Fei, Brian Quanz, Jun Huan
IWANN
2009
Springer
14 years 2 months ago
Identifying Gene Ontology Areas for Automated Enrichment
Biomedical ontologies provide a commonly accepted scheme for the characterization of biological concepts that enable knowledge sharing and integration. Updating and maintaining an ...
Catia Pesquita, Tiago Grego, Francisco M. Couto
SIGMOD
1998
ACM
99views Database» more  SIGMOD 1998»
13 years 12 months ago
CURE: An Efficient Clustering Algorithm for Large Databases
Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clust...
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim