A thesis on utilizing machine learning models to predict material hardship

A thesis on utilizing machine learning models to predict material hardship

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Applied Economics, 2023.

书目详细资料
主要作者: Das, Tirtha
其他作者: Quadria, Taufiq Hasan
格式: Thesis
语言:English
出版: Brac University 2024
主题:
Material hardship
Logistic regression
Vector machine model
Social equity
Machine-learning
Regression analysis > Data processing
在线阅读:http://hdl.handle.net/10361/22944
id 10361-22944
record_format dspace
spelling 10361-229442024-05-27T21:04:59Z A thesis on utilizing machine learning models to predict material hardship Das, Tirtha Quadria, Taufiq Hasan Department of Economics and Social Sciences, Brac University Material hardship Logistic regression Vector machine model Social equity Machine-learning Regression analysis--Data processing This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Applied Economics, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 36-38). This thesis addresses the concern of material hardship, defined by a paucity in resources necessary to fulfil fundamental needs, especially affecting children and families. Drawing insights from studies on the determinants of material hardship, including low income, unemployment, single parenthood, and financial literacy, the research employs a comprehensive methodology. It incorporates the integration of machine learning techniques to enhance the predictive capacity of identifying at-risk populations. The methodology advocates for a holistic approach, incorporating the transformative potential of machine learning techniques such as Logistic Regression, Non-Linear Support Vector Machine Model, Decision Tree etc. This paper highlights the transformative potential of machine learning in proficiently analyzing extensive datasets to recognize complex patterns. The positive correlation established between higher financial literacy, bill paying tendency, management of finances and improved economic outcomes stresses the potential impact of targeted financial education initiatives. Moreover, the research emphasizes the need for a proactive stance, advocating for the development of predictive models using historical evidence to anticipate and address material hardship in a timely manner. The inferences emphasize the necessity for targeted interventions and proactive measures, promoting social equity, resilience, and contributing to broader poverty reduction strategies Tirtha Das M. in Economics 2024-05-27T10:32:48Z 2024-05-27T10:32:48Z ©2023 2023-12 Thesis ID 22275001 http://hdl.handle.net/10361/22944 en Brac University theses are protected by copyright. This may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 45 pages application/pdf Brac University
institution Brac University
collection Institutional Repository
language English
topic Material hardship
Logistic regression
Vector machine model
Social equity
Machine-learning
Regression analysis--Data processing
spellingShingle Material hardship
Logistic regression
Vector machine model
Social equity
Machine-learning
Regression analysis--Data processing
Das, Tirtha
A thesis on utilizing machine learning models to predict material hardship
description This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Applied Economics, 2023.
author2 Quadria, Taufiq Hasan
author_facet Quadria, Taufiq Hasan
Das, Tirtha
format Thesis
author Das, Tirtha
author_sort Das, Tirtha
title A thesis on utilizing machine learning models to predict material hardship
title_short A thesis on utilizing machine learning models to predict material hardship
title_full A thesis on utilizing machine learning models to predict material hardship
title_fullStr A thesis on utilizing machine learning models to predict material hardship
title_full_unstemmed A thesis on utilizing machine learning models to predict material hardship
title_sort thesis on utilizing machine learning models to predict material hardship
publisher Brac University
publishDate 2024
url http://hdl.handle.net/10361/22944
work_keys_str_mv AT dastirtha athesisonutilizingmachinelearningmodelstopredictmaterialhardship
AT dastirtha thesisonutilizingmachinelearningmodelstopredictmaterialhardship
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