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PR
2002
134views more  PR 2002»
15 years 4 months ago
Interactive clustering and merging with a new fuzzy expected value
7 Major problems exist in both crisp and fuzzy clustering algorithms. The fuzzy c-means type of algorithms use weights determined by a power m of inverse distances that remains
Carl G. Looney
ICMCS
2005
IEEE
100views Multimedia» more  ICMCS 2005»
15 years 10 months ago
Fuzzy image segmentation using shape information
Results of any clustering algorithm are highly sensitive to features that limit their generalization and hence provide a strong motivation to integrate shape information into the ...
Mohammed Ameer Ali, Gour C. Karmakar, Laurence S. ...
140
Voted
RECOMB
2008
Springer
16 years 4 months ago
Computation of Median Gene Clusters
Whole genome comparison based on gene order has become a popular approach in comparative genomics. An important task in this field is the detection of gene clusters, i.e. sets of g...
Sebastian Böcker, Katharina Jahn, Julia Mixta...
AI
2006
Springer
15 years 8 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda
ICML
2010
IEEE
15 years 3 months ago
Multiple Non-Redundant Spectral Clustering Views
Many clustering algorithms only find one clustering solution. However, data can often be grouped and interpreted in many different ways. This is particularly true in the high-dim...
Donglin Niu, Jennifer G. Dy, Michael I. Jordan