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KDD
2009
ACM
208views Data Mining» more  KDD 2009»
14 years 8 months ago
A principled and flexible framework for finding alternative clusterings
The aim of data mining is to find novel and actionable insights in data. However, most algorithms typically just find a single (possibly non-novel/actionable) interpretation of th...
Zijie Qi, Ian Davidson
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
14 years 1 months ago
A multi-objective approach to discover biclusters in microarray data
The main motivation for using a multi–objective evolutionary algorithm for finding biclusters in gene expression data is motivated by the fact that when looking for biclusters ...
Federico Divina, Jesús S. Aguilar-Ruiz
ACMSE
2006
ACM
14 years 1 months ago
Automatic quality assessment of Affymetrix GeneChip data
Computing reliable gene expression levels from microarray experiments is a sophisticated process with many potential pitfalls. Quality control is one of the most important steps i...
Steffen Heber, Beate Sick
BMCBI
2007
237views more  BMCBI 2007»
13 years 7 months ago
FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data
Background: Data clustering analysis has been extensively applied to extract information from gene expression profiles obtained with DNA microarrays. To this aim, existing cluster...
Limin Fu, Enzo Medico
ADBIS
2007
Springer
132views Database» more  ADBIS 2007»
14 years 1 months ago
Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Rayner Alfred, Dimitar Kazakov