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Graduate Theses, Dissertations, and Problem Reports

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Machine Learning

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Full-Text Articles in Social and Behavioral Sciences

Three Essays On Health Economics And Policy Evaluation, Shishir Shakya Jan 2020

Three Essays On Health Economics And Policy Evaluation, Shishir Shakya

Graduate Theses, Dissertations, and Problem Reports

This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances …


Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data, Christopher A. Ramezan Jan 2019

Object-Based Supervised Machine Learning Regional-Scale Land-Cover Classification Using High Resolution Remotely Sensed Data, Christopher A. Ramezan

Graduate Theses, Dissertations, and Problem Reports

High spatial resolution (HR) (1m – 5m) remotely sensed data in conjunction with supervised machine learning classification are commonly used to construct land-cover classifications. Despite the increasing availability of HR data, most studies investigating HR remotely sensed data and associated classification methods employ relatively small study areas. This work therefore drew on a 2,609 km2, regional-scale study in northeastern West Virginia, USA, to investigates a number of core aspects of HR land-cover supervised classification using machine learning. Issues explored include training sample selection, cross-validation parameter tuning, the choice of machine learning algorithm, training sample set size, and feature selection. A …