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Original title:
A note on weighted combination methods for probability estimation
Authors: Sečkárová, Vladimíra
Document type: Papers
Conference/Event: The 3rd International Workshop on Scalable Decision Making: Uncertainty, Imperfection, Deliberation held in conjunction with ECML/PKDD 2013, Prague (CZ), 2013-09-23 / 2013-09-23
Year: 2013
Language: eng
Abstract: To successfully learn from the information provided by avail- able information sources, the choice of automatic method combining them into one aggregate result plays an important role. To respect the reliability in the source’s performance each of them is assigned a weight, often subjectively influenced. To overcome this issue, we briefly describe the method based on Bayesian decision theory and elements of infor- mation theory. In particular we consider discrete-type information, rep- resented by probability mass functions (pmfs) and obtain an aggregate result, which has also form of pmf. This result of decision making pro- cess is found to be a weighted linear combination of available information. Besides the brief description of the novel method, the paper focuses on its comparison with other combination methods. Since we consider the available information and unknown aggregate as pmfs, we mainly focus on the case when the parameter of binomial distribution is of interest and the sources provide appropriate pmfs.
Keywords: binomial distribution; Kerridge inaccuracy; maximum entropy principle; parameter estimation; weighting methods
Project no.: GA13-13502S (CEP), SVV 267315
Funding provider: GA ČR, GA UK
Host item entry: Preprints of the 3rd International Workshop on Scalable Decision Making held in conjunction with ECML/PKDD 2013, ISBN 978-80-903834-8-7
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2013/AS/seckarova-a note on weighted combination methods for probability estimation.pdf
Original record: http://hdl.handle.net/11104/0224701
Permalink: http://www.nusl.cz/ntk/nusl-156641
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers
Authors: Sečkárová, Vladimíra
Document type: Papers
Conference/Event: The 3rd International Workshop on Scalable Decision Making: Uncertainty, Imperfection, Deliberation held in conjunction with ECML/PKDD 2013, Prague (CZ), 2013-09-23 / 2013-09-23
Year: 2013
Language: eng
Abstract: To successfully learn from the information provided by avail- able information sources, the choice of automatic method combining them into one aggregate result plays an important role. To respect the reliability in the source’s performance each of them is assigned a weight, often subjectively influenced. To overcome this issue, we briefly describe the method based on Bayesian decision theory and elements of infor- mation theory. In particular we consider discrete-type information, rep- resented by probability mass functions (pmfs) and obtain an aggregate result, which has also form of pmf. This result of decision making pro- cess is found to be a weighted linear combination of available information. Besides the brief description of the novel method, the paper focuses on its comparison with other combination methods. Since we consider the available information and unknown aggregate as pmfs, we mainly focus on the case when the parameter of binomial distribution is of interest and the sources provide appropriate pmfs.
Keywords: binomial distribution; Kerridge inaccuracy; maximum entropy principle; parameter estimation; weighting methods
Project no.: GA13-13502S (CEP), SVV 267315
Funding provider: GA ČR, GA UK
Host item entry: Preprints of the 3rd International Workshop on Scalable Decision Making held in conjunction with ECML/PKDD 2013, ISBN 978-80-903834-8-7
Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2013/AS/seckarova-a note on weighted combination methods for probability estimation.pdf
Original record: http://hdl.handle.net/11104/0224701
Permalink: http://www.nusl.cz/ntk/nusl-156641
The record appears in these collections:
Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers
Record created 2013-10-10, last modified 2021-11-24