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Dissertations / Theses on the topic 'Classification methods'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Jamain, Adrien. "Meta-analysis of classification methods." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.413686.

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2

Chzhen, Evgenii. "Plug-in methods in classification." Thesis, Paris Est, 2019. http://www.theses.fr/2019PESC2027/document.

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Ce manuscrit étudie plusieurs problèmes de classification sous contraintes. Dans ce cadre de classification, notre objectif est de construire un algorithme qui a des performances aussi bonnes que la meilleure règle de classification ayant une propriété souhaitée. Fait intéressant, les méthodes de classification de type plug-in sont bien appropriées à cet effet. De plus, il est montré que, dans plusieurs configurations, ces règles de classification peuvent exploiter des données non étiquetées, c'est-à-dire qu'elles sont construites de manière semi-supervisée. Le Chapitre 1 décrit deux cas parti

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3

Felldin, Markus. "Machine Learning Methods for Fault Classification." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-183132.

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This project, conducted at Ericsson AB, investigates the feasibility of implementing machine learning techniques in order to classify dump files for more effi cient trouble report routing. The project focuses on supervised machine learning methods and in particular Bayesian statistics. It shows that a program utilizing Bayesian methods can achieve well above random prediction accuracy. It is therefore concluded that machine learning methods may indeed become a viable alternative to human classification of trouble reports in the near future.<br>Detta examensarbete, utfört på Ericsson AB, ämnar

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4

Gimati, Yousef M. T. "Bootstrapping techniques to improve classification methods." Thesis, University of Leeds, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.401072.

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5

Clibbon, Alex P. "Methods of classification of the cardiotocogram." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:550bb5ea-bee8-4eb8-95e2-f16c54d7cd68.

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This Thesis compares CTG classification techniques proposed in the literature and their potential extensions. A comparison between four classifiers previously assessed - Adaboost, Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machine (SVM) - and two proposed classifiers - Bayesian ANN (BANN), Relevance Vector Machine - was conducted using a database of 7,568 cases and two open source databases. The Random Forest (RF) achieved the highest average result and was proposed as a benchmark classifier. The proposal to use model certainty to introduce a third, unclassified, clas

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6

Kobayashi, Izumi. "Randomized ensemble methods for classification trees." Diss., Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02sep%5FKobayashi.pdf.

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Thesis (Ph. D. in Operations Research)--Naval Postgraduate School, September 2002.<br>Dissertation supervisor: Samuel E. Buttrey. Includes bibliographical references (p. 117-119). Also available online.

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7

Baker, Jonathan Peter. "Methods of Music Classification and Transcription." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3330.

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We begin with an overview of some signal processing terms and topics relevant to music analysis including facts about human sound perception. We then discuss common objectives of music analysis and existing methods for accomplishing them. We conclude with an introduction to a new method of automatically transcribing a piece of music from a digital audio signal.

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8

Zeggada, Abdallah. "Advanced classification methods for UAV imagery." Doctoral thesis, Università degli studi di Trento, 2018. https://hdl.handle.net/11572/367947.

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The rapid technological advancement manifested lately in the remote sensing acquisition platforms has triggered many benefits in favor of automated territory control and monitoring. In particular, unmanned aerial vehicles (UAVs) technology has drawn a lot of attention, providing an efficient solution especially in real-time applications. This is mainly motivated by their capacity to collect extremely high resolution (EHR) data over inaccessible areas and limited coverage zones, thanks to their small size and rapidly deployable flight capability, notwithstanding their ease of use and affordabil

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9

Zeggada, Abdallah. "Advanced classification methods for UAV imagery." Doctoral thesis, University of Trento, 2018. http://eprints-phd.biblio.unitn.it/2943/1/thesis_disclaimer.pdf.

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The rapid technological advancement manifested lately in the remote sensing acquisition platforms has triggered many benefits in favor of automated territory control and monitoring. In particular, unmanned aerial vehicles (UAVs) technology has drawn a lot of attention, providing an efficient solution especially in real-time applications. This is mainly motivated by their capacity to collect extremely high resolution (EHR) data over inaccessible areas and limited coverage zones, thanks to their small size and rapidly deployable flight capability, notwithstanding their ease of use and affordabil

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10

Lugo, A. "ORDINAL CLASSIFICATION TREES: METHODS AND APPLICATION." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/344318.

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During my PhD in Biomedical Statistics, I focused my research on the study of ordinal classification tree methodology, to be applied in case of ordinal categorical outcome, and all the statistical and computational methods related to them. Then, I provided an application on the set of controls of Italian case-control studies, in order to identify the profiles of individuals according to their total energy intake, and to their consumption of red meat and processed meat. Introduction to classification trees Tree-based methods are non parametric regression methods belonging to a group of tech

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11

Beghtol, Clare. "James Duff Brown's Subject Classification and Evaluation Methods for Classification Systems." dLIST, 2004. http://hdl.handle.net/10150/106250.

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James Duff Brown (1862-1914), an important figure in librarianship in late nineteenth and early twentieth century England, made contributions in many areas of his chosen field. His Subject Classification (SC), however, has not received much recognition for its theoretical and practical contributions to bibliographic classification theory and practice in the twentieth century. This paper discusses some of the elements of SC that both did and did not inform future bibliographic classification work, considers some contrasting evaluation methods in the light of advances in bibliographic classifica

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12

Ravindran, Sourabh. "Physiologically Motivated Methods For Audio Pattern Classification." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14066.

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Human-like performance by machines in tasks of speech and audio processing has remained an elusive goal. In an attempt to bridge the gap in performance between humans and machines there has been an increased effort to study and model physiological processes. However, the widespread use of biologically inspired features proposed in the past has been hampered mainly by either the lack of robustness across a range of signal-to-noise ratios or the formidable computational costs. In physiological systems, sensor processing occurs in several stages. It is likely the case that signal features and bio

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13

Kim, Heeyoung. "Statistical methods for function estimation and classification." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/44806.

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This thesis consists of three chapters. The first chapter focuses on adaptive smoothing splines for fitting functions with varying roughness. In the first part of the first chapter, we study an asymptotically optimal procedure to choose the value of a discretized version of the variable smoothing parameter in adaptive smoothing splines. With the choice given by the multivariate version of the generalized cross validation, the resulting adaptive smoothing spline estimator is shown to be consistent and asymptotically optimal under some general conditions. In the second part, we derive the asympt

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14

Lohr, Marisa. "Methods for the genetic classification of languages." Thesis, University of Cambridge, 1999. https://www.repository.cam.ac.uk/handle/1810/251688.

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15

BRHANIE, BEKALU MULLU. "Multi-Label Classification Methods for Image Annotation." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13725.

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16

Saldanha, Richard A. "Graph-theoretic methods in discrimination and classification." Thesis, University of Oxford, 1998. https://ora.ox.ac.uk/objects/uuid:3a06dee1-00e9-4b56-be8e-e991a570ced6.

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This thesis is concerned with the graphical modelling of multivariate data. The main aim of graphical modelling is to provide an easy to understand visual representation of, often complex, data relationships by fitting graphs to data. The graphs consist of nodes denoting random variables and connecting lines or edges are used to depict variable dependencies. Equivalently, the absence of particular edges in a graph describe conditional independencies between random variables. The resulting structure is called a conditional independence graph. The use of conditional independence graphs as a guid

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17

Gretton, Arthur Lindsey. "Kernel methods for classification and signal separation." Thesis, University of Cambridge, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615875.

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18

Cope, James S. "Computational methods for the classification of plants." Thesis, Kingston University, 2014. http://eprints.kingston.ac.uk/28759/.

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Plants are of fundamental importance to life on Earth. The shapes of leaves, petals and whole plants are of great significance to plant science, as they can help to distinguish between different species, to measure plant health, and even to model climate change. The current availability of botanists is increasingly failing to meet the growing demands for their expertise. These demands range from amateurs desiring help in identifying plants, to agricultural applications such as automated weeding systems, and to the cataloguing of biodiversity for conservational purposes. This thesis aims to hel

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19

Fong, Wai Lam. "Numerical methods for classification and image restoration." HKBU Institutional Repository, 2013. http://repository.hkbu.edu.hk/etd_ra/1488.

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20

Varnavas, Andreas Soteriou. "Signal processing methods for EEG data classification." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/11943.

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21

Hofmeyr, David. "Projection methods for clustering and semi-supervised classification." Thesis, Lancaster University, 2016. http://eprints.lancs.ac.uk/87219/.

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This thesis focuses on data projection methods for the purposes of clustering and semi-supervised classification, with a primary focus on clustering. A number of contributions are presented which address this problem in a principled manner; using projection pursuit formulations to identify subspaces which contain useful information for the clustering task. Projection methods are extremely useful in high dimensional applications, and situations in which the data contain irrelevant dimensions which can be counterinformative for the clustering task. The final contribution addresses high dimension

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22

Isaksson, Ola. "Classification of Flying Qualities with Machine Learning Methods." Thesis, KTH, Flygdynamik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302145.

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The primary objective of this thesis is to evaluate the prospect of machine learning methods being used to classify flying qualities based on simulator data (with the focus being on pitch maneuvers). If critical flying qualities could be identified earlier in the verification process, they can be further invested in and focused on with less cost for design changes of the flight control system. Information from manned simulations with given flying quality levels are used to create a replication of the performed pitch maneuver in a desktop simulator. The generated flight data is represented by d

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23

Bazin, Alexander Ian. "On probabilistic methods for object description and classification." Thesis, University of Southampton, 2006. https://eprints.soton.ac.uk/263161/.

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This thesis extends the utility of probabilistic methods in two diverse domains: multimodal biometrics and machine inspection. The attraction for this approach is that it is easily understood by those using such a system; however the advantages extend beyond the ease of human utility. Probabilistic measures are ideal for combination since they are guaranteed to be within a fixed range and are generally well scaled. We describe the background to probabilistic techniques and critique common implementations used by practitioners. We then set out our novel probabilistic framework for classificatio

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24

Wang, Rui. "Comparisons of Classification Methods in Efficiency and Robustness." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1345564802.

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25

He, Ping. "Classification methods and applications to mass spectral data." HKBU Institutional Repository, 2005. http://repository.hkbu.edu.hk/etd_ra/593.

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26

Hung, Jane Yen. "Making computer vision Methods accessible for cell classification." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/121894.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, 2018<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 107-113).<br>Computers are better than ever at extracting information from visual media like images, which are especially powerful in biology. The field of computer vision tries to take advantage of this fact and use computational algorithms to analyze image data and gain higher level understanding. Recent advances in machine learning such as deep learning based architectures have greatly expanded their potential.

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27

Pasolli, Edoardo. "Active learning methods for classification and regression problems." Doctoral thesis, Università degli studi di Trento, 2011. https://hdl.handle.net/11572/368080.

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In the pattern recognition community, one of the most critical problems in the design of supervised classification and regression systems is given by the quality and the quantity of the exploited training samples (ground-truth). This problem is particularly important in such applications in which the process of training sample collection is an expensive and time consuming task subject to different sources of errors. Active learning represents an interesting approach proposed in the literature to address the problem of ground-truth collection, in which training samples are selected in an iterat

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28

Pasolli, Edoardo. "Active learning methods for classification and regression problems." Doctoral thesis, University of Trento, 2011. http://eprints-phd.biblio.unitn.it/638/1/PhD-Thesis-Pasolli.pdf.

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In the pattern recognition community, one of the most critical problems in the design of supervised classification and regression systems is given by the quality and the quantity of the exploited training samples (ground-truth). This problem is particularly important in such applications in which the process of training sample collection is an expensive and time consuming task subject to different sources of errors. Active learning represents an interesting approach proposed in the literature to address the problem of ground-truth collection, in which training samples are selected in an iterat

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29

Lamont, Morné Michael Connell. "Binary classification trees : a comparison with popular classification methods in statistics using different software." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52718.

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Thesis (MComm) -- Stellenbosch University, 2002.<br>ENGLISH ABSTRACT: Consider a data set with a categorical response variable and a set of explanatory variables. The response variable can have two or more categories and the explanatory variables can be numerical or categorical. This is a typical setup for a classification analysis, where we want to model the response based on the explanatory variables. Traditional statistical methods have been developed under certain assumptions such as: the explanatory variables are numeric only and! or the data follow a multivariate normal distributio

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30

Randolph, Tami Rochele. "Image compression and classification using nonlinear filter banks." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/13439.

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31

Gasanova, Tatiana [Verfasser]. "Novel methods for text preprocessing and classification / Tatiana Gasanova." Ulm : Universität Ulm. Fakultät für Ingenieurwissenschaften und Informatik, 2015. http://d-nb.info/1075568404/34.

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32

Wang, Wei. "Predictive modeling based on classification and pattern matching methods." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0019/MQ51498.pdf.

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33

Delmege, James W. "CLASS : a study of methods for coarse phonetic classification /." Online version of thesis, 1988. http://hdl.handle.net/1850/10449.

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34

Ding, Yunfei. "Application of Clustering and Classification Methods to Pattern Recognition." Thesis, University of Sheffield, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511954.

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35

Le, Truc Duc. "Machine Learning Methods for 3D Object Classification and Segmentation." Thesis, University of Missouri - Columbia, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13877153.

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<p> Object understanding is a fundamental problem in computer vision and it has been extensively researched in recent years thanks to the availability of powerful GPUs and labelled data, especially in the context of images. However, 3D object understanding is still not on par with its 2D domain and deep learning for 3D has not been fully explored yet. In this dissertation, I work on two approaches, both of which advances the state-of-the-art results in 3D classification and segmentation.</p><p> The first approach, called MVRNN, is based multi-view paradigm. In contrast to MVCNN which does no

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36

Andrews, Suzanne L. D. (Suzanne Lois Denise). "A classification of carbon footprint methods used by companies." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/51642.

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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.<br>Includes bibliographical references (leaves 50-54).<br>The percent increase in greenhouse gas (GHG) concentration in the atmosphere can be harmful to the environment. There is no single preferred method for measuring GHG output. How can a company classify and choose an appropriate method? This thesis offers a classification of current methods used by companies to measure their GHG output.<br>by Suzanne L. D. Andrews.<br>M.Eng.in Logistics

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37

Olfert, Jason Scott. "On new methods of ultra-fine particle mass classification." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614186.

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38

Булах, В. А., Л. О. Кіріченко, and Т. А. Радівілова. "Classification of Multifractal Time Series by Decision Tree Methods." Thesis, КНУ, 2018. http://openarchive.nure.ua/handle/document/5840.

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The article considers classification task of model fractal time series by the methods of machine learning. To classify the series, it is proposed to use the meta algorithms based on decision trees. To modeling the fractal time series, binomial stochastic cascade processes are used. Classification of time series by the ensembles of decision trees models is carried out. The analysis indicates that the best results are obtained by the methods of bagging and random forest which use regression trees.

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39

Newling, James. "Novel methods of supernova classification and type probability estimation." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/11174.

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Future photometric surveys will provide vastly more supernovae than have presently been observed, the majority of which will not be spectroscopically typed. Key to extracting information from these future datasets will be the efficient use of light-curves. In the first part of this thesis we introduce two methods for distinguishing type Ia supernovae from their contaminating counterparts, kernel density estimation and boosting. In the second half of this thesis we shift focus from classification to the related problem of type probability estimation, and ask how best to use type probabilities.

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40

Kelley, Edward T. II. "Comparative Analysis of Obesity Classification Methods in Aging Adults." Bowling Green State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1429283749.

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41

Towey, David John. "SPECT imaging and automatic classification methods in movement disorders." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/11182.

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This work investigates neuroimaging as applied to movement disorders by the use of radionuclide imaging techniques. There are two focuses in this work: 1) The optimisation of the SPECT imaging process including acquisition and image reconstruction. 2) The development and optimisation of automated analysis techniques The first part has included practical measurements of camera performance using a range of phantoms. Filtered back projection and iterative methods of image reconstruction were compared and optimised. Compensation methods for attenuation and scatter are assessed. Iterative methods a

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42

Nasser, Sara. "Fuzzy methods for meta-genome sequence classification and assembly." abstract and full text PDF (free order & download UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3307706.

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43

Phung, Le Son. "Deep Learning Methods for Health Data Imputation and Classification." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25007.

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The analysis of digital health data with machine learning models can be used in clinical applications such as computer aided diagnosis and population health classifi- cation. However, the quality of machine learning is highly dependent on the quality of the underlying data. The quality of a dataset can be negatively impacted by missing values, which are a common occurrence in medical and health datasets, and can cause biased estimations or loss of statistical power. Data imputation (or reconstruction) is one way to reduce missing data, however current methods are generally based around stat

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44

Danielsson, Benjamin. "A Study on Text Classification Methods and Text Features." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-159992.

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When it comes to the task of classification the data used for training is the most crucial part. It follows that how this data is processed and presented for the classifier plays an equally important role. This thesis attempts to investigate the performance of multiple classifiers depending on the features that are used, the type of classes to classify and the optimization of said classifiers. The classifiers of interest are support-vector machines (SMO) and multilayer perceptron (MLP), the features tested are word vector spaces and text complexity measures, along with principal component anal

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45

Puodzius, Cassius. "Data-driven malware classification assisted by machine learning methods." Electronic Thesis or Diss., Rennes 1, 2022. https://ged.univ-rennes1.fr/nuxeo/site/esupversions/3dabb48c-b635-46a5-bcbe-23992a2512ec.

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Historiquement, l'analyse des logiciels malveillants (ou MW) a fortement fait appel au savoir-faire humain pour la création manuelle de signatures permettant de détecter et de classer les MW. Cette procédure est très coûteuse et prend beaucoup de temps, ce qui ne permet pas de faire face aux scénario modernes de cybermenaces. La solution consiste à automatiser largement l'analyse des MW. Dans ce but, la classification des MW permet d'optimiser le traitement de grands corpus de MW en identifiant les ressemblances entre des instances similaires. La classification des MW est donc une activité clé

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Gewehr, Jan Erik. "New Methods for the Prediction and Classification of Protein Domains." Diss., lmu, 2007. http://nbn-resolving.de/urn:nbn:de:bvb:19-80287.

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Ekong, Udeme Essien. "Development of computational intelligence methods to deal with classification problems." Thesis, King's College London (University of London), 2016. https://kclpure.kcl.ac.uk/portal/en/theses/development-of-computational-intelligence-methods-to-deal-with-classi-cation-problems(0f04e932-0e3d-4309-a21f-1e2f6df6d29d).html.

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In the thesis presented here, variations of two very prominent machine learning techniques, the Neural Network (NN) and Support Vector Machine (SVM) are used in an attempt to solve two classification problems. Classification involves the assignment of an unknown object into a pre-determined group which consists of a set of preclassified objects with similar features to that unknown object. The main theme of the research conducted in this thesis involves investigation into existing and proposed classifier architectures to improve the classification performance for certain research problems. The

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48

Kandaswamy, Krishna Kumar [Verfasser]. "Sequence function classification by machine learning methods / Krishna Kumar Kandaswamy." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2012. http://d-nb.info/1023624257/34.

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49

Nilsson, Daniel. "Investigating the effect of microarray preprocessing methods on tumor classification." Thesis, Uppsala universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-258951.

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Mohamed, Ghada. "Text classification in the BNC using corpus and statistical methods." Thesis, Lancaster University, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.658020.

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The main part of this thesis sets out to develop a system of categories within a text typology. Although there exist many different approaches to the classification of text into categories, this research fills a gap in the literature, as most work on text classification is based on features external to the text such as the text's purpose, the aim of discourse, and the medium of communication. Text categories that have been set up based on some external features are not linguistically defined. In consequence, texts that belong to the same type are not necessarily similar in their linguistic for

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