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Optimum Probability Estimation from Empirical Distributions

Probability estimation is important for the application of probabilistic models as well as for any evaluation in IR. We discuss the interdependencies between parameter estimation and certain properties of probabilistic models: dependence assumptions, binary vs. non-binary features, estimation sample selection. Then we define an optimum estimate for binary features which can be applied to various typical estimation problems in IR. A method for computing this estimate using empirical data is described. Some experiments show the applicability of our method, whereas comparable approaches are partially based on false assumptions or yield biased estimates.

Identiferoai:union.ndltd.org:DUETT/oai:DUETT:duett-04232004-101837
Date23 April 2004
CreatorsFuhr, Norbert ; Huether, Hubert
Contributorsnone
PublisherGerhard-Mercator-Universitaet Duisburg
Source SetsDissertations and other Documents of the Gerhard-Mercator-University Duisburg
LanguageGerman
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://www.ub.uni-duisburg.de/ETD-db/theses/available/duett-04232004-101837/
Rightsunrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. Hiermit erteile ich der Universitaet Duisburg das nicht-ausschliessliche Recht unter den unten angegebenen Bedingungen, meine Dissertation, Staatsexamens- oder Diplomarbeit, meinen Forschungs- oder Projektbericht zu veroeffentlichen und zu archivieren. Ich behalte das Urheberrecht und das Recht das Dokument zu veroeffentlichen und in anderen Arbeiten weiterzuverwenden.

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