Rückstieß, Thomas and Osendorfer, Christian and Smagt van der, Patrick (2012) Minimizing Data Consumption with Sequential Online Feature Selection. International Journal of Machine Learning and Cybernetics, April 2012. Springer. DOI: 10.1007/s13042-012-0092-x ISSN 1868-8071
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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
Item URL in elib: | https://elib.dlr.de/81300/ | ||||||||||||
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Document Type: | Article | ||||||||||||
Title: | Minimizing Data Consumption with Sequential Online Feature Selection | ||||||||||||
Authors: |
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Date: | 2012 | ||||||||||||
Journal or Publication Title: | International Journal of Machine Learning and Cybernetics | ||||||||||||
Refereed publication: | Yes | ||||||||||||
Open Access: | No | ||||||||||||
Gold Open Access: | No | ||||||||||||
In SCOPUS: | Yes | ||||||||||||
In ISI Web of Science: | Yes | ||||||||||||
Volume: | April 2012 | ||||||||||||
DOI : | 10.1007/s13042-012-0092-x | ||||||||||||
Publisher: | Springer | ||||||||||||
ISSN: | 1868-8071 | ||||||||||||
Status: | Published | ||||||||||||
Keywords: | Reinforcement learning, Feature selection, Classification | ||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||
HGF - Program: | Space | ||||||||||||
HGF - Program Themes: | Space Technology | ||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||
DLR - Program: | R SY - Technik für Raumfahrtsysteme | ||||||||||||
DLR - Research theme (Project): | R - Vorhaben Terrestrische Assistenz-Robotik | ||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||
Institutes and Institutions: | Institute of Robotics and Mechatronics (until 2012) | ||||||||||||
Deposited By: | Grebenstein, Dr. sc. Markus | ||||||||||||
Deposited On: | 21 Feb 2013 13:37 | ||||||||||||
Last Modified: | 06 Sep 2019 15:30 |
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