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ICANN
2009
Springer
13 years 6 months ago
Mining Rules for the Automatic Selection Process of Clustering Methods Applied to Cancer Gene Expression Data
Different algorithms have been proposed in the literature to cluster gene expression data, however there is no single algorithm that can be considered the best one independently on...
André C. A. Nascimento, Ricardo Bastos Cava...
ICDAR
2011
IEEE
12 years 8 months ago
Graph Clustering-Based Ensemble Method for Handwritten Text Line Segmentation
—Handwritten text line segmentation on real-world data presents significant challenges that cannot be overcome by any single technique. Given the diversity of approaches and the...
Vasant Manohar, Shiv Naga Prasad Vitaladevuni, Hua...
JMLR
2010
99views more  JMLR 2010»
13 years 3 months ago
Characterization, Stability and Convergence of Hierarchical Clustering Methods
We study hierarchical clustering schemes under an axiomatic view. We show that within this framework, one can prove a theorem analogous to one of J. Kleinberg (Kleinberg, 2002), i...
Gunnar Carlsson, Facundo Mémoli
BMCBI
2010
164views more  BMCBI 2010»
13 years 6 months ago
Merged consensus clustering to assess and improve class discovery with microarray data
Background: One of the most commonly performed tasks when analysing high throughput gene expression data is to use clustering methods to classify the data into groups. There are a...
T. Ian Simpson, J. Douglas Armstrong, Andrew P. Ja...
JMLR
2010
225views more  JMLR 2010»
13 years 3 months ago
Hartigan's Method: k-means Clustering without Voronoi
Hartigan's method for k-means clustering is the following greedy heuristic: select a point, and optimally reassign it. This paper develops two other formulations of the heuri...
Matus Telgarsky, Andrea Vattani