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» Classification of microarray data using gene networks
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ICML
2008
IEEE
16 years 3 months ago
Discriminative parameter learning for Bayesian networks
Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
NN
2000
Springer
161views Neural Networks» more  NN 2000»
15 years 2 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
BMCBI
2006
144views more  BMCBI 2006»
15 years 2 months ago
Association algorithm to mine the rules that govern enzyme definition and to classify protein sequences
Background: The number of sequences compiled in many genome projects is growing exponentially, but most of them have not been characterized experimentally. An automatic annotation...
Shih-Hau Chiu, Chien-Chi Chen, Gwo-Fang Yuan, Thy-...
DSN
2007
IEEE
15 years 9 months ago
What Supercomputers Say: A Study of Five System Logs
If we hope to automatically detect and diagnose failures in large-scale computer systems, we must study real deployed systems and the data they generate. Progress has been hampere...
Adam J. Oliner, Jon Stearley
GIS
2004
ACM
16 years 3 months ago
A new approach for a topographic feature-based characterization of digital elevation data
Triangular Irregular Network (TIN) and Regular Square Grid (RSG) are widely used for representing 2.5 dimensional spatial data. However, these models are not defined from the topo...
Eric Saux, Ki-Joune Li, Min-Hwan Kim, Rémy ...