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Dissertations / Theses on the topic 'Auc-Roc'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

Zheng, Shimin. "The ROC Curve and the Area under the Curve (AUC)." Digital Commons @ East Tennessee State University, 2017. https://dc.etsu.edu/etsu-works/139.

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2

Lu, Qing. "Methods for Designing and Forming Predictive Genetic Tests." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1212197560.

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3

Yuan, Yan. "Empirical Likelihood-Based NonParametric Inference for the Difference between Two Partial AUCS." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/math_theses/32.

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Compare the accuracy of two continuous-scale tests is increasing important when a new test is developed. The traditional approach that compares the entire areas under two Receiver Operating Characteristic (ROC) curves is not sensitive when two ROC curves cross each other. A better approach to compare the accuracy of two diagnostic tests is to compare the areas under two ROC curves (AUCs) in the interested specificity interval. In this thesis, we have proposed bootstrap and empirical likelihood (EL) approach for inference of the difference between two partial AUCs. The empirical likelihood rat

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4

Huang, Xin. "Bootstrap and Empirical Likelihood-based Semi-parametric Inference for the Difference between Two Partial AUCs." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/math_theses/54.

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With new tests being developed and marketed, the comparison of the diagnostic accuracy of two continuous-scale diagnostic tests are of great importance. Comparing the partial areas under the receiver operating characteristic curves (pAUC) is an effective method to evaluate the accuracy of two diagnostic tests. In this thesis, we study the semi-parametric inference for the difference between two pAUCs. A normal approximation for the distribution of the difference between two pAUCs has been derived. The empirical likelihood ratio for the difference between two pAUCs is defined and its asymptoti

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5

Sun, Fangfang. "Semi-parametric inference for the partial area under the ROC curve." unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-11192008-113213/.

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Thesis (M.S.)--Georgia State University, 2008.<br>Title from file title page. Gengsheng Qin, committee chair; Yu-Sheng Hsu, Yixin Fang, Yuanhui Xiao, committee members. Description based on contents viewed July 22, 2009. Includes bibliographical references (p. 29-30).

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6

Zhou, Haochuan. "Statistical Inferences for the Youden Index." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_diss/5.

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In diagnostic test studies, one crucial task is to evaluate the diagnostic accuracy of a test. Currently, most studies focus on the Receiver Operating Characteristics Curve and the Area Under the Curve. On the other hand, the Youden index, widely applied in practice, is another comprehensive measurement for the performance of a diagnostic test. For a continuous-scale test classifying diseased and non-diseased groups, finding the Youden index of the test is equivalent to maximize the sum of sensitivity and specificity for all the possible values of the cut-point. This dissertation concentrates

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7

Xu, Ping. "Evaluation of Repeated Biomarkers: Non-parametric Comparison of Areas under the Receiver Operating Curve Between Correlated Groups Using an Optimal Weighting Scheme." Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4261.

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Receiver Operating Characteristic (ROC) curves are often used to evaluate the prognostic performance of a continuous biomarker. In a previous research, a non-parametric ROC approach was introduced to compare two biomarkers with repeated measurements. An asymptotically normal statistic, which contains the subject-specific weights, was developed to estimate the areas under the ROC curve of biomarkers. Although two weighting schemes were suggested to be optimal when the within subject correlation is 1 or 0 by the previous study, the universal optimal weight was not determined. We modify this asym

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8

Bitara, Matúš. "Srovnání heuristických a konvenčních statistických metod v data miningu." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-400833.

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The thesis deals with the comparison of conventional and heuristic methods in data mining used for binary classification. In the theoretical part, four different models are described. Model classification is demonstrated on simple examples. In the practical part, models are compared on real data. This part also consists of data cleaning, outliers removal, two different transformations and dimension reduction. In the last part methods used to quality testing of models are described.

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9

Khamesipour, Alireza. "IMPROVED GENE PAIR BIOMARKERS FOR MICROARRAY DATA CLASSIFICATION." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1573.

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The Top Scoring Pair (TSP) classifier, based on the notion of relative ranking reversals in the expressions of two marker genes, has been proposed as a simple, accurate, and easily interpretable decision rule for classification and class prediction of gene expression profiles. We introduce the AUC-based TSP classifier, which is based on the Area Under the ROC (Receiver Operating Characteristic) Curve. The AUCTSP classifier works according to the same principle as TSP but differs from the latter in that the probabilities that determine the top scoring pair are computed based on the relati

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10

Wang, Binhuan. "Statistical Evaluation of Continuous-Scale Diagnostic Tests with Missing Data." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/math_diss/8.

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The receiver operating characteristic (ROC) curve methodology is the statistical methodology for assessment of the accuracy of diagnostics tests or bio-markers. Currently most widely used statistical methods for the inferences of ROC curves are complete-data based parametric, semi-parametric or nonparametric methods. However, these methods cannot be used in diagnostic applications with missing data. In practical situations, missing diagnostic data occur more commonly due to various reasons such as medical tests being too expensive, too time consuming or too invasive. This dissertation aims to

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11

Albakour, Subhy. "Stream-automl : automated machine learning overimbalanced data streams for bipartite ranking problems." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAT015.

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Malgré sa popularité dans la littérature scientifique, l’apprentissage en ligne doit encore concrétiser son utilité pratique dans les applications industrielles. Vu que l’apprentissage en ligne gère les flux incessants de données volumineuses, à haute vélocité et en évolution constante par conception, le marketing en ligne semble être le candidat favori pour que l’apprentissage en ligne fasse son entrée dans l’industrie. Dans ce contexte, l’état de l’art de l’apprentissage en ligne n’a qu’une utilité limitée, car il se concentre principalement sur les problèmes de classification, tandis que le

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12

Yang, Hanfang. "Jackknife Emperical Likelihood Method and its Applications." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/math_diss/9.

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In this dissertation, we investigate jackknife empirical likelihood methods motivated by recent statistics research and other related fields. Computational intensity of empirical likelihood can be significantly reduced by using jackknife empirical likelihood methods without losing computational accuracy and stability. We demonstrate that proposed jackknife empirical likelihood methods are able to handle several challenging and open problems in terms of elegant asymptotic properties and accurate simulation result in finite samples. These interesting problems include ROC curves with missing data

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13

Yu, Daoping. "Early Stopping of a Neural Network via the Receiver Operating Curve." Digital Commons @ East Tennessee State University, 2010. https://dc.etsu.edu/etd/1732.

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This thesis presents the area under the ROC (Receiver Operating Characteristics) curve, or abbreviated AUC, as an alternate measure for evaluating the predictive performance of ANNs (Artificial Neural Networks) classifiers. Conventionally, neural networks are trained to have total error converge to zero which may give rise to over-fitting problems. To ensure that they do not over fit the training data and then fail to generalize well in new data, it appears effective to stop training as early as possible once getting AUC sufficiently large via integrating ROC/AUC analysis into the training pro

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14

Hansén, Jacob, and Axel Gustafsson. "A Study on Comparison Websites in the Airline Industry and Using CART Methods to Determine Key Parameters in Flight Search Conversion." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254309.

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This bachelor thesis in applied mathematics and industrial engineering and management aimed to identify relationships between search parameters in flight comparison search engines and the exit conversion rate, while also investigating how the emergence of such comparison search engines has impacted the airline industry. To identify such relationships, several classification models were employed in conjunction with several sampling methods to produce a predictive model using the program R. To investigate the impact of the emergence of comparison websites, Porter's 5 forces and a SWOT - analysis

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15

Mackových, Marek. "Analýza experimentálních EKG." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-241981.

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This thesis is focused on the analysis of experimental ECG records drawn up in isolated rabbit hearts and aims to describe changes in EKG caused by ischemia and left ventricular hypertrophy. It consists of a theoretical analysis of the problems in the evaluation of ECG during ischemia and hypertrophy, and describes an experimental ECG recording. Theoretical part is followed by a practical section which describes the method for calculating morphological parameters, followed by ROC analysis to evaluate their suitability for the classification of hypertrophy and at the end is focused on classific

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16

Pospíšil, Lukáš. "Analýza ROC křivek zvukových signálů a jejich srovnání." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-316445.

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This thesis deals with oportunity of ROC curve usage in the description of methods that work with sound signals. Specifically, it focuses on ways of detecting of stress in speech signals. The detection itselfs is done in a range of frequencies of the sound signal. There is also a classifier designed using ROC curves that decides whether the input signal is stressed or not. The output of this thesis are findings gathered from analyses and also some recommendation based on those analyses.

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17

Plch, Vít. "Detekce fibrilace síní v EKG." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-402125.

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This diploma thesis deals with detection of atrial fibrillation from HRV, classification of Poincare map and in the end the divide into two groups, one with detected atrial fibrillation and one not. The result is the decision on which variables are statistically significant for the identification of atrial fibrillations and which are not, and classification of the ECG signals.

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18

Li, Yi. "A Generalization of AUC to an Ordered Multi-Class Diagnosis and Application to Longitudinal Data Analysis on Intellectual Outcome in Pediatric Brain-Tumor Patients." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/math_diss/1.

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Receiver operating characteristic (ROC) curves have been widely used in evaluation of the goodness of the diagnostic method in many study fields, such as disease diagnosis in medicine. The area under the ROC curve (AUC) naturally became one of the most used variables in gauging the goodness of the diagnosis (Mossman, Somoza 1991). Since medical diagnosis often is not dichotomous, the ROC curve and AUC need to be generalized to a multi-dimensional case. The generalization of AUC to multi-class case has been studied by many researchers in the past decade. Most recently, Nakas & Yiannoutsos (2

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19

Tang, Hong. "A Comparison of Two Modeling Techniques in Customer Targeting For Bank Telemarketing." 2014. http://scholarworks.gsu.edu/math_theses/139.

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Customer targeting is the key to the success of bank telemarketing. To compare the flexible discriminant analysis and the logistic regression in customer targeting, a survey dataset from a Portuguese bank was used. For the flexible discriminant analysis model, the backward elimination of explanatory variables was used with several rounds of manual re-defining of dummy variables. For the logistic regression model, the automatic stepwise selection was performed to decide which explanatory variables should be left in the final model. Ten-fold stratified cross validation was performed to estimate

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20

Werner, Carola. "Nichtparametrische Analyse von diagnostischen Tests." Doctoral thesis, 2006. http://hdl.handle.net/11858/00-1735-0000-000D-F21E-A.

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21

Lange, Katharina. "Nichtparametrische Analyse diagnostischer Gütemaße bei Clusterdaten." Doctoral thesis, 2011. http://hdl.handle.net/11858/00-1735-0000-000D-F1D1-B.

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22

Bednář, Ondřej. "Srovnání modifikací predikčních bankrotních modelů." Master's thesis, 2017. http://www.nusl.cz/ntk/nusl-431270.

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The goal of this theses is to compare existing bankruptcy prediction models with its new modification unique for this work, which could perform better than its competition. Proposed model is logit-based and consists of the combination of variables used in Altman´s and Ohlson´s models. The final model is estimated for medium sized companies in EU which aren´t publicly traded. This model achieved prediction accuracy of 97,1% (97.4% for healthy and 91.1% for bankrupt compa-nies) on its original dataset. As expected, when verified on new dataset, the accu-racy dropped but still reaches 97.1% (99.3

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23

Cruz, Rafael Cunha. "Determinants of bankruptcy in the portuguese shoe manufacturing industry." Master's thesis, 2020. http://hdl.handle.net/10400.14/32108.

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O propósito desta tese é investigar o fenómeno das falências na indústria do calçado em Portugal, contruindo um modelo capaz de prever este fenómeno com 1 ano de antecedência e analisando que variáveis têm mais influência nesse desfecho. Para tal, uma abordagem baseada em modelos binários Logit, foi usada para construir (e mais tarde validar) 5 modelos baseados numa amostra de 2,073 empresas do sector industrial do calçado em Portugal, entre 2006 e 2018, onde se registou um total de 422 ocorrências que classificamos como falências. Validamos que 2 dos nossos modelos registaram uma capacidade d

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24

Stones, George. "Predicting Community-based Methadone Maintenance Treatment (MMT) Outcome." Thesis, 2012. http://hdl.handle.net/1807/34932.

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This was a retrospective study of a community-based methadone maintenance treatment (MMT) program in Toronto. Participants (N = 170) were federally sentenced adult male offenders admitted to this voluntary program between 1997 and 2009 while subject to community supervision following incarceration. The primary investigation examined correlates of treatment responsivity, with principal outcome measures including MMT clients’ rates of: (i) illicit drug use; and (ii) completion of conditional (parole) or statutory release (SR). For a subset (n = 74), recidivism rates were examined after a 9-year

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25

Melo, André Pestana Sampaio e. "Cálculo do limite superior para a capacidade discriminante de modelos preditivos baseados na informação disponível – variáveis dependentes dicotómicas." Master's thesis, 2011. http://hdl.handle.net/10362/8293.

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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação.<br>Quando se avalia o poder discriminante de um determinado modelo (com variável dependente dicotómica) recorrendo à curva ROC, é usual representar-se no mesmo gráfico o “Modelo perfeito” e o “Modelo aleatório” enquanto limites teóricos (superior e inferior) à capacidade discriminante. O presente trabalho propõe o cálculo de um limite superior complementar, derivado dos dados e conceptualmente distinto do obtido via o “Modelo perfeito”. Este novo limite designar-se-á “Capacidad

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