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» Unsupervised Analysis for Decipherment Problems
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BMCBI
2011
14 years 5 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
DICTA
2007
15 years 5 days ago
K-means Clustering for Classifying Unlabelled MRI Data
Texture analysis of the liver for the diagnosis of cirrhosis is usually region-of-interest (ROI) based. Integrity of the label of ROI data may be a problem due to sampling. This p...
Gobert N. Lee, Hiroshi Fujita
FUZZIEEE
2007
IEEE
15 years 5 months ago
Using Orders of Magnitude and Nominal Variables to Construct Fuzzy Partitions
— The application of Qualitative Reasoning to Learning Algorithms can provide these models with the capability of automate common-sense and expert reasoning. Learning algorithms ...
Cati Olmo, Germán Sánchez, Francesc ...
ICML
2001
IEEE
15 years 11 months ago
Constrained K-means Clustering with Background Knowledge
Clustering is traditionally viewed as an unsupervised method for data analysis. However, in some cases information about the problem domain is available in addition to the data in...
Kiri Wagstaff, Claire Cardie, Seth Rogers, Stefan ...
CCIA
2007
Springer
15 years 4 months ago
Semantic disambiguation of taxonomies
Polysemy is one of the most difficult problems when dealing with natural language resources. Consequently, automated ontology learning from textual sources (such as web resources) ...
David Sánchez, Antonio Moreno