CCBias: An Event Detection Optimization Framework

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dc.contributor.authorFaridani, Theo H.
dc.date.accessioned2019-11-07T16:10:08Z
dc.date.available2019-11-07T16:10:08Z
dc.date.issued2019
dc.description35 pages
dc.description.abstractWe present a software, CCBias, to assist researchers in observing events of all kinds. Given characteristic information about a population of objects and observational methods, CCBias can generate synthetic observational data. CCBias can also recommend search strategies if told what observational outcomes are desirable. Lastly, CCBias can estimate the bias in real data by transforming the problem of identifying bias into a problem of estimating model parameters. We demonstrate the strengths and weaknesses of CCBias in a case study focused on planetary defense. CCBias is written in the Python programming language.en_US
dc.identifier.urihttps://hdl.handle.net/1794/25017
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsCreative Commons BY-NC-ND 4.0-US
dc.subjectPhysicsen_US
dc.subjectObservationen_US
dc.subjectComputer Scienceen_US
dc.subjectCensored Dataen_US
dc.subjectBiasen_US
dc.subjectData Scienceen_US
dc.titleCCBias: An Event Detection Optimization Framework
dc.typeThesis/Dissertation

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