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Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 10 of 10 for “"Bayesian logistic regression"”.
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Modeling the NCAA Tournament Through Bayesian Logistic Regression
… variables. We use an MCMC approach and logistic regression along with several model selection techniques to arrive at models for predicting the winner of each game. When given the 63 actual games in the 2012 tournament, eight of our models performed as well as Pomeroy's rating system and …
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The influence of probability of detection when modeling species occurrence using GIS and survey data
… analysis (ENFA) predicted presence better than logistic regression and Bayesian logistic regression models. Database collections of observations have limited value as input for modeling because of the lack of absence data. Without knowledge of detectability, it is unknown whether non-detection …
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Genome-wide microbial phylogeny reconstruction with polytomy identification
… employs a machine learning technique, BLR (Bayesian logistic regression) classifier to identify possible bifurcating subtrees as polytomies or not from the result trees generated from ComPhy. We have developed a set of two phylogenetic analysis applications, which are fast and robust for …
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A Narrative-Focused Machine Learning Approach to Predicting Feature Film Success
… The predictive analysis was conducted using a logistic regression model fitted on augmented data split into training and testing sets. Inferential analysis was performed through Bayesian logistic regression, calculating causal estimates and 80% credible intervals derived from four chains with …
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Count regression models with a misclassified binary covariate : a Bayesian approach.
… are inevitable in a variety of regression applications. Fallible measurement methods are often used when infallible methods are either expensive or not available. Ignoring mismeasurement will result in biased estimates for the associated regression parameters. The models …
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Application of Hyper-geometric Hypothesis-based Quantication and Markov Blanket Feature Selection Methods to Generate Signals for Adverse Drug Reaction Detection
… It is proposed as an alternative to the emerging Bayesian logistic regressionmethod for detecting adverse drug reaction.Experiments have been conducted using the Adverse Event Reporting System (AERS) main-tained by the US Food and Drug Administration. The results showed that the performanceof the …
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Finding patterns in features and observations : new machine learning models with applications in computational criminology, marketing, and medicine
… sets for binary classification. The first method Bayesian Rule Set (BRS) uses a Bayesian framework with priors that favor small models. The Bayesian priors also bring significant computational benefits to MAP inferences by reducing the search space and restraining the sampling chain within …
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Bayesian Designs For Early Phase Clinical Trials With Novel Target Agents
<p>My dissertation mainly focus on Bayesian designs for early phase clinical trials with novel target agents. It includes three specific topics: (1) reviewing novel phase I clinical trial designs and comparing their operating characteristics; (2) Proposing a Bayesian optimal phase II clinical trial …
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Urban Expressway Safety and Efficiency Evaluation and Improvement using Big Data
… and their performances compared. Multi-level Bayesian ridge regression was utilized to deal with the multicollinearity issue in the modeling process. While all of the congestion measures indicated congestion was a contributing factor to crash occurrence in the peak hours, they suggested that …
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Analysis of Factors that Influence Member Turnover in a Health Insurance Plan
In this research, we implement a multiple logistic regression model in which the coefficients of indicator variables are constrained to be zero or positive. By doing this, the contribution of each variable to the failure probability can be assessed. Due to this restriction on the coefficients, a …