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» A Learning Classifier Approach to Tomography
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117
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HIS
2004
15 years 5 months ago
Hybrid Learning Scheme for Data Mining Applications
Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directl...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
EMNLP
2004
15 years 5 months ago
Learning Hebrew Roots: Machine Learning with Linguistic Constraints
The morphology of Semitic languages is unique in the sense that the major word-formation mechanism is an inherently non-concatenative process of interdigitation, whereby two morph...
Ezra Daya, Dan Roth, Shuly Wintner
BMCBI
2010
224views more  BMCBI 2010»
15 years 4 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
163
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ENGL
2007
136views more  ENGL 2007»
15 years 3 months ago
Multilayered Evolutionary Architecture for Behaviour Arbitration in Cognitive Agents
— In this work, an hybrid, self-configurable, multilayered and evolutionary subsumption architecture for cognitive agents is developed. Each layer of the multilayered architectur...
Oscar Javier Romero López
TREC
2004
15 years 5 months ago
Feature Generation, Feature Selection, Classifiers, and Conceptual Drift for Biomedical Document Triage
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...