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EDBT
2008
ACM
167views Database» more  EDBT 2008»
14 years 8 months ago
HISSCLU: a hierarchical density-based method for semi-supervised clustering
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Christian Böhm, Claudia Plant
NN
2006
Springer
163views Neural Networks» more  NN 2006»
13 years 8 months ago
Machine learning approaches for estimation of prediction interval for the model output
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...
Durga L. Shrestha, Dimitri P. Solomatine
CORR
2010
Springer
249views Education» more  CORR 2010»
13 years 8 months ago
Performance Analysis of Spectral Clustering on Compressed, Incomplete and Inaccurate Measurements
Spectral clustering is one of the most widely used techniques for extracting the underlying global structure of a data set. Compressed sensing and matrix completion have emerged a...
Blake Hunter, Thomas Strohmer
ISI
2008
Springer
13 years 8 months ago
A locality model of the evolution of blog networks
We present a model of evolution of large social networks. Our model is based on the local nature of communication: a node's communication energy is spend mostly within it'...
Mark K. Goldberg, Malik Magdon-Ismail, Stephen Kel...
BMEI
2008
IEEE
13 years 10 months ago
Clustering of High-Dimensional Gene Expression Data with Feature Filtering Methods and Diffusion Maps
The importance of gene expression data in cancer diagnosis and treatment by now has been widely recognized by cancer researchers in recent years. However, one of the major challen...
Rui Xu, Steven Damelin, Boaz Nadler, Donald C. Wun...