693 search results - page 42 / 139 » Outlier-aware robust clustering |
ICARCV
2002
IEEE
15 years 2 months ago
2002
IEEE
Although the least median of squares (LMedS) method and the least trimmed squares (LTS) method are said to have a high breakdown point (50%), they can break down at unexpectedly l...
EACL
2003
ACL Anthology
14 years 11 months ago
2003
ACL Anthology
In this paper we discuss algorithms for clustering words into classes from unlabelled text using unsupervised algorithms, based on distributional and morphological information. We...
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BMCBI
2010
14 years 10 months ago
2010
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
BMCBI
2008
14 years 10 months ago
2008
Background: Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson corre...
BMCBI
2005
14 years 9 months ago
2005
Background: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determin...