Building a predictive model for poverty in Palestine using machine learning classification tools
Dissertant
Thesis advisor
University
Birzeit University
Faculty
Faculty of Graduate Studies
Department
Applied Statistics
University Country
Palestine (West Bank)
Degree
Master
Degree Date
2020
Arabic Abstract
تركز هذه الدراسة على مقارنة نماذج للتنبؤ بحالة الفقر في فلسطين باستخدام البيانات المقدمة من مسح الإنفاق و الاستهلاك 2017 و الذي أجراه الجهاز المركزي للإحصاء الفلسطيني تستخدم هذه الدراسة العوامل الديموغرافية في بناء نماذج الانحدار و مصنف تعلم الآلة (شجرة القرار للتنبؤ بحالة الفقر في الأسرة.
وجدت الدراسة العديد من المتغيرات الديموغرافية لرب الأسرة و متغيرات تتعلق بظروف الأسرة و المسكن التي يمكن استخدامها للتنبؤ بحالة الفقر للأسرة و أظهرت الدراسة أن شجرة القرار قدمت أعلى قيم في مقاييس الدقة و الصدق بين جميع النماذج الأربعة المستخدمة.
English Abstract
This study focuses on comparing competive models in predicting poverty status in Palestine using data provided by The Palestine Expenditure and Consumption Survey, PECS 2017, which is carried by the Palestinian Central Bureau of Statistics (PCBS).
It expands on demographic factors by utilizing them in regression models and a machine learning classifier (decision tree) to predict the poverty status of a household.
The study finds numerous demographic variables for the head of household, housing, and household conditions that can be used in predicting the poverty status of a household.
The study showed that among the four models used, the decision tree provided the highest accuracy and validity indicators.
Main Subjects
Mathematics
Information Technology and Computer Science
No. of Pages
67
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Literature review.
Chapter Three : Methodology.
Chapter Four : Research findings.
Chapter Five : Conclusion.
References.
American Psychological Association (APA)
al-Gharabah, Ali. (2020). Building a predictive model for poverty in Palestine using machine learning classification tools. (Master's theses Theses and Dissertations Master). Birzeit University, Palestine (West Bank)
https://search.emarefa.net/detail/BIM-1412372
Modern Language Association (MLA)
al-Gharabah, Ali. Building a predictive model for poverty in Palestine using machine learning classification tools. (Master's theses Theses and Dissertations Master). Birzeit University. (2020).
https://search.emarefa.net/detail/BIM-1412372
American Medical Association (AMA)
al-Gharabah, Ali. (2020). Building a predictive model for poverty in Palestine using machine learning classification tools. (Master's theses Theses and Dissertations Master). Birzeit University, Palestine (West Bank)
https://search.emarefa.net/detail/BIM-1412372
Language
English
Data Type
Arab Theses
Record ID
BIM-1412372
