Ordinal Regression over Time Series Data, with an Application to Classifying Patient Vital Sign Quality

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dc.contributor.advisorJermaine, Christopher M.
dc.contributor.committeeMemberKavraki, Lydia E.
dc.contributor.committeeMemberNakhleh, Luay K.
dc.creatorMyers, Risa B
dc.date.accessioned2014-09-23T20:59:00Z
dc.date.available2014-09-23T20:59:00Z
dc.date.created2013-12
dc.date.issued2013-06-05
dc.date.submittedDecember 2013
dc.date.updated2014-09-23T20:59:01Z
dc.description.abstractThis research is concerned with modeling the vital sign data that are present in many electronic health records. Such vital sign data are typically represented as a (possibly multidimensional) time series. My goal is to label these time series with one o
dc.format.mimetypeapplication/pdf
dc.identifier.citationMyers, Risa B. "Ordinal Regression over Time Series Data, with an Application to Classifying Patient Vital Sign Quality." (2013) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/77232">https://hdl.handle.net/1911/77232</a>.
dc.identifier.urihttps://hdl.handle.net/1911/77232
dc.language.isoeng
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.
dc.subjectTime series
dc.subjectMachine learning
dc.subjectVital sign
dc.subjectBiomedical data
dc.subjectBayesian statistics
dc.titleOrdinal Regression over Time Series Data, with an Application to Classifying Patient Vital Sign Quality
dc.typeThesis
dc.type.materialText
thesis.degree.departmentComputer Science
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
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