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CSDA
2008
128views more  CSDA 2008»
13 years 7 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
ESANN
2006
13 years 8 months ago
Adaptive Sensor Modelling and Classification using a Continuous Restricted Boltzmann Machine (CRBM)
A probabilistic, ``neural'' approach to sensor modelling and classification is described, performing local data fusion in a wireless system for embedded sensors using a ...
Tong Boon Tang, Alan F. Murray
CORR
2006
Springer
105views Education» more  CORR 2006»
13 years 7 months ago
Generalization error bounds in semi-supervised classification under the cluster assumption
We consider semi-supervised classification when part of the available data is unlabeled. These unlabeled data can be useful for the classification problem when we make an assumpti...
Philippe Rigollet
SOFTWARE
2002
13 years 7 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
BMCBI
2008
179views more  BMCBI 2008»
13 years 7 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao