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IGARSS
2009
13 years 3 months ago
Endmember Extraction from Hyperspectral Imagery using a Parallel Ensemble Approach with Consensus Analysis
We have explored in this paper a framework to test in a quantitative manner the stability of different endmember extraction and spectral unmixing algorithms based on the concept o...
Fermin Ayuso, Javier Setoain, Manuel Prieto, Chris...
JBI
2004
171views Bioinformatics» more  JBI 2004»
13 years 7 months ago
Consensus Clustering and Functional Interpretation of Gene Expression Data
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus s...
Paul Kellam, Stephen Swift, Allan Tucker, Veronica...
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
13 years 7 months ago
Are approximation algorithms for consensus clustering worthwhile?
Consensus clustering has emerged as one of the principal clustering problems in the data mining community. In recent years the theoretical computer science community has generated...
Michael Bertolacci, Anthony Wirth
ECIR
2007
Springer
13 years 7 months ago
A Hierarchical Consensus Architecture for Robust Document Clustering
Abstract. A major problem encountered by text clustering practitioners is the difficulty of determining a priori which is the optimal text representation and clustering technique f...
Xavier Sevillano, Germán Cobo, Francesc Al&...
ALENEX
2008
142views Algorithms» more  ALENEX 2008»
13 years 7 months ago
Consensus Clustering Algorithms: Comparison and Refinement
Consensus clustering is the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. Cast ...
Andrey Goder, Vladimir Filkov
DILS
2004
Springer
13 years 11 months ago
Heterogeneous Data Integration with the Consensus Clustering Formalism
Meaningfully integrating massive multi-experimental genomic data sets is becoming critical for the understanding of gene function. We have recently proposed methodologies for integ...
Vladimir Filkov, Steven Skiena
ICDM
2005
IEEE
150views Data Mining» more  ICDM 2005»
13 years 11 months ago
Combining Multiple Clusterings by Soft Correspondence
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
GECCO
2007
Springer
167views Optimization» more  GECCO 2007»
13 years 11 months ago
An improved restricted growth function genetic algorithm for the consensus clustering of retinal nerve fibre data
This paper describes an extension to the Restricted Growth Function grouping Genetic Algorithm applied to the Consensus Clustering of a retinal nerve fibre layer data-set. Consens...
Stephen Swift, Allan Tucker, Jason Crampton, David...
ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
13 years 12 months ago
Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Tao Li, Chris H. Q. Ding, Michael I. Jordan
ICDM
2007
IEEE
170views Data Mining» more  ICDM 2007»
13 years 12 months ago
Consensus Clusterings
In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
Nam Nguyen, Rich Caruana