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» Classification with Belief Decision Trees
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ESANN
2006
13 years 6 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
BMCBI
2008
141views more  BMCBI 2008»
13 years 5 months ago
Functional discrimination of membrane proteins using machine learning techniques
Background: Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amin...
M. Michael Gromiha, Yukimitsu Yabuki
BMCBI
2007
146views more  BMCBI 2007»
13 years 5 months ago
Spatial location and its relevance for terminological inferences in bio-ontologies
Background: An adequate and expressive ontological representation of biological organisms and their parts requires formal reasoning mechanisms for their relations of physical aggr...
Stefan Schulz, Kornél G. Markó, Udo ...
IJSI
2008
156views more  IJSI 2008»
13 years 5 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker