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» Learning Classifiers from Semantically Heterogeneous Data
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CEC
2008
IEEE
13 years 9 months ago
Learning defect classifiers for visual inspection images by neuro-evolution using weakly labelled training data
This article presents results from experiments where a detector for defects in visual inspection images was learned from scratch by EANT2, a method for evolutionary reinforcement l...
Nils T. Siebel, Gerald Sommer
BMCBI
2005
131views more  BMCBI 2005»
13 years 7 months ago
Regularized Least Squares Cancer Classifiers from DNA microarray data
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
Nicola Ancona, Rosalia Maglietta, Annarita D'Addab...
AO
2005
75views more  AO 2005»
13 years 7 months ago
A multi-layered ontology for comparing relationship semantics in conceptual models of databases
Relationships are an integral part of the design of a database. Comparing and integrating relationships from heterogeneous databases requires that the relationships be mapped to ea...
Sandeep Purao, Veda C. Storey
IJCAI
2003
13 years 8 months ago
Learning to Classify Texts Using Positive and Unlabeled Data
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
Xiaoli Li, Bing Liu
BMCBI
2006
150views more  BMCBI 2006»
13 years 7 months ago
Instance-based concept learning from multiclass DNA microarray data
Background: Various statistical and machine learning methods have been successfully applied to the classification of DNA microarray data. Simple instance-based classifiers such as...
Daniel P. Berrar, Ian Bradbury, Werner Dubitzky