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  1. International Journal of Machine Learning and Cybernetics
  2. International Journal of Machine Learning and Cybernetics : Volume 4
  3. International Journal of Machine Learning and Cybernetics : Volume 4, Issue 3, June 2013
  4. Minimizing data consumption with sequential online feature selection
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International Journal of Machine Learning and Cybernetics : Volume 8
International Journal of Machine Learning and Cybernetics : Volume 7
International Journal of Machine Learning and Cybernetics : Volume 6
International Journal of Machine Learning and Cybernetics : Volume 5
International Journal of Machine Learning and Cybernetics : Volume 4
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 6, December 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 5, October 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 4, August 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 3, June 2013
An enhanced XCS rule discovery module using feature ranking
Design of custom-made stacked patch antennas: a machine learning approach
On the structure of definable sets in covering approximation spaces
Spatial pooling for greyscale images
Parameter selection algorithm with self adaptive growing neural network classifier for diagnosis issues
Minimizing data consumption with sequential online feature selection
Lattice-valued information systems based on dominance relation
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 2, April 2013
International Journal of Machine Learning and Cybernetics : Volume 4, Issue 1, February 2013
International Journal of Machine Learning and Cybernetics : Volume 3
International Journal of Machine Learning and Cybernetics : Volume 2
International Journal of Machine Learning and Cybernetics : Volume 1

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International journal of machine learning and cybernetics

Article

Minimizing data consumption with sequential online feature selection

Content Provider SpringerLink
Author Rückstieß, Thomas Osendorfer, Christian van der Smagt, Patrick
Copyright Year 2012
Abstract In most real-world information processing problems, data is not a free resource. Its acquisition is often expensive and time-consuming. We investigate how such cost factors can be included in supervised classification tasks by deriving classification as a sequential decision process and making it accessible to reinforcement learning. Depending on previously selected features and the internal belief of the classifier, a next feature is chosen by a sequential online feature selection that learns which features are most informative at each time step. Experiments on toy datasets and a handwritten digits classification task show significant reduction in required data for correct classification, while a medical diabetes prediction task illustrates variable feature cost minimization as a further property of our algorithm.
Starting Page 235
Ending Page 243
Page Count 9
File Format PDF
ISSN 18688071
Journal International Journal of Machine Learning and Cybernetics
Volume Number 4
Issue Number 3
e-ISSN 1868808X
Language English
Publisher Springer-Verlag
Publisher Date 2012-04-27
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Reinforcement learning Feature selection Classification Computational Intelligence Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics Statistical Physics, Dynamical Systems and Complexity Systems Biology Pattern Recognition
Content Type Text
Resource Type Article
Subject Artificial Intelligence Computer Vision and Pattern Recognition Software
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