Physical Sciences and Mathematics Commons^™

On Improving Performance Of The Binary Logistic Regression Classifier, Michael Chang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Logistic Regression, being both a predictive and an explanatory method, is one of the most commonly used statistical and machine learning method in almost all disciplines. There are many situations, however, when the accuracies of the fitted model are low for predicting either the success event or the failure event. Several statistical and machine learning approaches exist in the literature to handle these situations. This thesis presents several new approaches to improve the performance of the fitted model, and the proposed methods have been applied to real datasets.

Transformations of predictors is a common approach in fitting multiple linear and …

Identifying Risk Factors Related To Premature Birth Through Binary Logistic And Proportional Odds Ordinal Logistic Regression, Clayton Elwood

Electronic Theses and Dissertations

Premature birth has been identified as the single greatest cause of death worldwide in children under the age of five. This thesis will implement binary logistic regression and proportional odds ordinal logistic regression to predict different levels of premature birth and identify associated risk factors. The models will be built from the Center for Disease Control and Prevention's 2014 Vital Statistics Natality Birth Data containing nearly 4 million live births within the United States. Odds ratios and confidence intervals on risk factors were produced utilizing binary logistic regression.

The Role Of Glucose Level On The Performance Of The Framingham Risk Score, Uohna June Thiessen

Walden Dissertations and Doctoral Studies

Cardiovascular diseases (CVD) are responsible for more deaths than any other disease, continue to threaten the quality of life for many, and is a major burden to the health care system. The Framingham Heart Study (FHS) identified the major CVD risk factors that became essential to effective CVD screening strategies and the Framingham Risk Score (FRS), is used to assess CVD risk. Based on the concepts of the health behavior model and CVD as a cardiometabolic disorder, multivariate logistic regression analysis was used to evaluate the association between fasting blood glucose (FBG) levels and a CHD event, and to determine …