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» Clustering functional data with the SOM algorithm
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ECML
2006
Springer
15 years 7 months ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
128
Voted
VDA
2010
169views Visualization» more  VDA 2010»
15 years 6 months ago
Techniques for precision-based visual analysis of projected data
The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection techniques such as PCA, MDS, and SOM can be used to map high-dimensional data t...
Tobias Schreck, Tatiana von Landesberger, Sebastia...
IJCNN
2000
IEEE
15 years 8 months ago
EM Algorithms for Self-Organizing Maps
eresting web-available abstracts and papers on clustering: An Analysis of Recent Work on Clustering Algorithms (1999), Daniel Fasulo : This paper describes four recent papers on cl...
Tom Heskes, Jan-Joost Spanjers, Wim Wiegerinck
BMCBI
2008
142views more  BMCBI 2008»
15 years 4 months ago
Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification
Background: In the present investigation, we have used an exhaustive metabolite profiling approach to search for biomarkers in recombinant Aspergillus nidulans (mutants that produ...
Irene Kouskoumvekaki, Zhiyong Yang, Svava Ó...
ICDM
2003
IEEE
158views Data Mining» more  ICDM 2003»
15 years 9 months ago
Combining Multiple Weak Clusterings
A data set can be clustered in many ways depending on the clustering algorithm employed, parameter settings used and other factors. Can multiple clusterings be combined so that th...
Alexander P. Topchy, Anil K. Jain, William F. Punc...