Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 23 for “"Classification and regression tree (CART)"”.
-
Using the classification and regression tree (CART) model for stock selection on the S&P 700
Traditionally, investment practitioners and academics alike have used stock fundamentals and a linear framework in order to predict future stock performance. This approach has been shown to have flaws as literature has shown that stock returns can exhibit non-linearity and involve complex relations …
-
Foster Care Placement Decisions: Is Race a Factor
… administrative data were analyzed using logistic regression analysis and Classification and Regression Tree (CART) analysis. Data revealed that the number of investigator home visits, the number of other investigator contacts, the number of previous indicated allegations, and infancy were the …
-
Use Of Multi-Gear Sampling To Improve Abundance Estimates Of Demersal Coregonids In The Laurentian Great Lakes
… Lake Whitefish (Coregonus clupeaformis) and Round Whitefish (Prosopium cylindraceum) play a vital role in both the Laurentian Great Lakes food webs and the commercial fishing industry. Hydroacoustic sampling has proven useful when performing stock assessments because hydroacoustics …
-
Benefits of a Tree-Based model for stock selection in a South African context
… performance of a stock relative to its benchmark and the stock's fundamental factors in a classical linear framework. However, these models have empirically been found to be unsuitable for capturing higher-order relationships between a stock's return relative to a benchmark and its fundamental …
-
The Influence of Heterogeneous Landscapes on Banded Mongoose (Mungos mungo) Behavior in Northern Botswana: Inferences about Infectious Disease Transmission
… by a complex suite of drivers with behavior and landscape dynamics contributing to epidemics across host-pathogen systems. However, our understanding of the interaction between landscape, behavior, and infectious disease remains limited. In the banded mongoose (Mungos mungo), a novel …
-
A computational model of prosody for Yorùbá text-to-speech synthesis
This work examines prosody modelling for the Standard Yorùbá (SY) language in the context of computer text-to-speech synthesis applications. The thesis of this research is that it is possible to develop a practical prosody model by using appropriate computational tools and techniques which combines …
-
Two Methodologies: How Well Can Universities Predict Retention
Student retention has been a long standing focus in higher education research with one of the earliest work dating back to 1937. Many researchers have proposed factors that affect a student's decision to depart from the university without successfully completing a degree. It is important to not …
-
Predicting favorable habitat for bobcats (Lynx rufus) in Iowa
… (Lynx rufus), once common in the prairie-woodland mosaic of the Midwest, were largely extirpated from the Corn Belt region by 1900. In the 1990's, sightings of bobcats in Iowa began to increase, and they are now abundant in southern Iowa. With the dramatic expansion of rowcrop agriculture …
-
Systems Pharmacology – Machine Learning Approaches in Profiling Oncology Drug Candidates
… however, the main focus is on the drug discovery and application of machine learning approaches in profiling oncology drug candidates for a select subset of validated targets in the oncogenesis pathways. In this study, we built in-silico predictive models to predict prospective drug candidates …
-
Object-Based Coastal Morphological Change Analysis Based on LiDAR and Hurricane Events
… hence they require further investigation and quantifying of coastal changes and responses. Light detection and ranging (LiDAR) is the most advanced technology to be widely used by researchers for coastal geomorphological studies. The purpose of this study is to apply an object-based …
-
From Field to Home: Assessing Air Infiltration and Soil Track-in Transport Pathways of Agricultural Pesticides into Farmworkers' Home and Identifying Risk Factors for Increased In-Home Pesticide Levels
Farmworkers and their families may experience increased levels of agricultural pesticides in their homes due to both (1) take-home/soil track-in on shoes, clothes and skin, and (2) air infiltration from nearby agriculture fields via agricultural pesticide drift in the vapor phase or adhered to …
-
PMU-Based Applications for Improved Monitoring and Protection of Power Systems
Monitoring and protection of power systems is a task that has manifold objectives. Amongst others, it involves performing data mining, optimizing available resources, assessing system stresses, and doing data conditioning. The role of PMUs in fulfilling these four objectives forms the basis of this …
-
Assessing Coastal Plain Wetland Composition using Advanced Spaceborne Thermal Emission and Reflection Radiometer Imagery
Establishing wetland gains and losses, delineating wetland boundaries, and determining their vegetative composition are major challenges that can be improved through remote sensing studies. In this study, we used the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to separate …
-
Neuropsychological and adaptive skills deficits in children with attention-deficit/hyperactivity disorder with and without comorbid fetal alcohol spectrum disorder
… this study was to compare the neuropsychological and adaptive skills profiles of children with Attention-Deficit/Hyperactivity Disorder (ADHD) with or without comorbid FASD in order to improve interventions for both of these populations. This study paid particular attention to neurological, …
-
Simulating Land Use Land Cover Change Using Data Mining and Machine Learning Algorithms
… this dissertation are to: (1) review the breadth and depth of land use land cover (LUCC) issues that are being addressed by the land change science community by discussing how an existing model, Purdue's Land Transformation Model (LTM), has been used to better understand these very important …
-
Machine learning models for functional impairment risk prediction in ischemic stroke patients
… models have been primarily developed based on regression models, which might not provide optimal predictive accuracy, especially when validated in an external cohort. Purpose: To evaluate the predictive accuracy of machine-learning (ML) models for predicting functional impairment risk in acute …
-
Distribution and predictors of non-indigenous marine species within South Africa's MPA network
… MPAs were surveyed intertidally for alien and invasive species. The intertidal zone was divided into high-, mid- and low-shore and surveys were conducted during spring low tide. The presence and location in the intertidal zone of alien and invasive species were recorded. Additionally, …
-
Early Predictors of Post-stroke Motor Recovery
… spontaneous biological recovery mechanisms and provision of intensive rehabilitation therapies, most stroke survivors experience persistent loss of upper extremity function which is directly related to reduced independence in activities of daily living and diminished quality of life. …
-
Soil-Landscape Modelling in an Andean Mountain Forest Region in Southern Ecuador
Soil-landscapes are diverse and complex due to the interaction of pedogenetic, geo-morphological and hydrological processes. The resulting soil profile reflects the balance of these processes in its properties. Early conceptual models have by now resulted into quantitative soil-landscape models …
-
An evidence-based algorithm for the rapid diagnosis of tuberculosis in HIV positive patients presenting to emergency centres
Background Tuberculosis remains a prevalent and deadly global disease. Diagnostic delays are partly due to reduced diagnostic performance of tuberculosis tests in HIV-positive people. The use of reliable pointof-care and near-patient diagnostic tests (e.g. urine lipoarabinomannan and point-of-care …
Page 1 of 2