Dimensionality reduction techniques with applications in Raman spectroscopy
department or school: Science, Irving K. Barber Faculty of (Okanagan)
department or school: Computer Science, Mathematics, Physics and Statistics, Department of (Okanagan)
data provider: DSpace
degree campus: UBCO
creator: Shreeves, Phillip
issued: 2020-09-03T15:02:34Z
issued: 2020
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: Raman spectroscopy (RS) is an optical interrogation method used to identify molecules through inelastic light scattering. This process often results in the acquired data having high dimensionality, as each observation has multiple intensities over hundreds of wave numbers. As a result, a common progression in the analysis of the spectra is to first reduce the dimensionality of the data before further examination. This thesis details the use of different dimensionality reduction techniques, including an extension of nonnegative matrix factorization (NMF). NMF is the process of decomposing the data matrix of interest into two lower rank matrices, with the constraint that all matrices must be nonnegative. This algorithm is extended in order to impose constraints on the model by decomposing the one of the specified matrices into two further nonnegative matrices, creating three in total. The application of this technique handles the previously discussed issues while also having added interpretability in comparison to principal component analysis (PCA), which is currently used in RS.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/75840
note: Dimensionality Reduction Techniqueswith Applications in RamanSpectroscopybyPhillip ShreevesB.Sc. Hons., The University of British Columbia, 2018M.Sc., The University of British Columbia, 2020A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinThe College of Graduate Studies(Mathematics)THE UNIVERSITY OF BRITISH COLUMBIA(Okanagan)August, 2020c© Phillip Shreeves, 2020The following individuals certify that they have read, and recommend tothe College of Graduate Studies for acceptance, a thesis/dissertation entitled:Dimensionality Reduction Techniqueswith Applications in Raman Spectroscopysubmitted by Phillip Shreeves in partial fulfilment of the requirements ofthe degree of Master of ScienceDr. Jeffrey L. Andrews, I. K. Barber School of Arts & SciencesSupervisorDr. Andrew Jirasek, I. K. Barber School of Arts & SciencesSupervisory Committee MemberDr. W. John Braun, I. K. Barber School of Arts & SciencesSupervisory Committee MemberDr. Sepideh Pakpour, School of EngineeringUniversity ExamineriiAbstractRaman spectroscopy (RS) is an optical interrogation method used toidentify molecules through inelastic light scattering. This process oftenresults in the acquired data having high dimensionality, as each observationhas multiple intensities over hundreds of wave numbers. As a result, a commonprogression in the analysis of the spectra is to first reduce the dimensionalityof the data before further examination. This thesis details the use of differentdimensionality reduction techniques, including an extension of nonnegativematrix factorization (NMF). NMF is the process of decomposing the datamatrix of interest into two lower rank matrices, with the constraint thatall matrices must be nonnegative. This algorithm is extended in order toimpose constraints on the model by decomposing the one of the specifiedmatrices into two further nonnegative matrices, creating three in total. Theapplication of this technique handles the previously dis…
has type: Thesis/Dissertation
date issued: 2020-09
is shown at: 10.14288/1.0394181
language: eng
degree discipline: Mathematics
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/75840