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CORR
2010
Springer
131views Education» more  CORR 2010»
15 years 6 months ago
A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering
We formulate weighted graph clustering as a prediction problem1 : given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. ...
Yevgeny Seldin
BMCBI
2005
124views more  BMCBI 2005»
15 years 6 months ago
Tools enabling the elucidation of molecular pathways active in human disease: Application to Hepatitis C virus infection
Background: The extraction of biological knowledge from genome-scale data sets requires its analysis in the context of additional biological information. The importance of integra...
David J. Reiss, Iliana Avila-Campillo, Vesteinn Th...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 7 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
ICDM
2005
IEEE
151views Data Mining» more  ICDM 2005»
16 years 7 days ago
A Framework for Semi-Supervised Learning Based on Subjective and Objective Clustering Criteria
In this paper, we propose a semi-supervised framework for learning a weighted Euclidean subspace, where the best clustering can be achieved. Our approach capitalizes on user-const...
Maria Halkidi, Dimitrios Gunopulos, Nitin Kumar, M...
GFKL
2004
Springer
135views Data Mining» more  GFKL 2004»
16 years 8 hour ago
KMC/EDAM: A New Approach for the Visualization of K-Means Clustering Results
In this work we introduce a method for classification and visualization. In contrast to simultaneous methods like e.g. Kohonen SOM this new approach, called KMC/EDAM, runs through...
Nils Raabe, Karsten Luebke, Claus Weihs