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» Learning on the Test Data: Leveraging Unseen Features
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ICML
2007
IEEE
16 years 15 days ago
Boosting for transfer learning
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu
BMCBI
2005
118views more  BMCBI 2005»
14 years 11 months ago
Feature selection and nearest centroid classification for protein mass spectrometry
Background: The use of mass spectrometry as a proteomics tool is poised to revolutionize early disease diagnosis and biomarker identification. Unfortunately, before standard super...
Ilya Levner
ICML
2010
IEEE
15 years 23 days ago
Bottom-Up Learning of Markov Network Structure
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Jesse Davis, Pedro Domingos
TREC
2004
15 years 1 months ago
Experience of Using SVM for the Triage Task in TREC 2004 Genomics Track
This paper reports our knowledge-ignorant machine learning approach to the triage task in TREC2004 genomics track, which is actually a text categorization problem. We applied Supp...
Dell Zhang, Wee Sun Lee
MICAI
2007
Springer
15 years 5 months ago
Building Fine Bayesian Networks Aided by PSO-Based Feature Selection
A successful interpretation of data goes through discovering crucial relationships between variables. Such a task can be accomplished by a Bayesian network. The dark side is that, ...
María del Carmen Chávez, Gladys Casa...