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.

Bibliografiske detaljer
Hovedforfatter:	Das, Tirtha
Andre forfattere:	Quadria, Taufiq Hasan
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2024
Fag:	Material hardship Logistic regression Vector machine model Social equity Machine-learning Regression analysis > Data processing
Online adgang:	http://hdl.handle.net/10361/22944

Lignende værker

Flood prediction using ensemble machine learning models
af: Rahman, Tanvir
Udgivet: (2024)

Where will you setup your business next?: a machine learning approach to suggest ideal geographical location for new restaurant establishment
af: Shihab, Ibne Farabi, et al.
Udgivet: (2018)

A machine learning approach to detect depression and anxiety using supervised learning
af: Ullas, Md Tahmidur Rahman, et al.
Udgivet: (2019)

Predicting stock market trend from twitter feed and building a framework for Bangladesh
af: Karim, Shabab, et al.
Udgivet: (2018)

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
af: Turjo, Aquib Abtahi, et al.
Udgivet: (2021)

Flood prediction using machine learning models
af: Syeed, Miah Mohammad Asif, et al.
Udgivet: (2022)

Statistical analysis of network data flows and predictions using statistical and machine learning regression models
af: Boateng, Albert, et al.
Udgivet: (2024)

Cardiovascular disease prediction model using Machine Learning Algorithm
af: Arefin Mirdha, MD Shamsul
Udgivet: (2023)

Prediction of bipolar disorder from mental episodes using machine learning approach
af: Tasmeem, Sumaiya, et al.
Udgivet: (2023)

Performance analysis of machine learning algorithms in resume recommendation systems
af: Hasan, Ibteaz, et al.
Udgivet: (2018)

Travel time prediction using machine learning and weather impact on traffic conditions
af: Deb, Bilash, et al.
Udgivet: (2018)

Predicting the length of stay in a hospital for a particular disease using machine learning algorithms
af: Imam, Saif
Udgivet: (2021)

Statistical analysis of network data flows and predictions using statistical and machine learning regression models
af: Boateng, Albert, et al.
Udgivet: (2024)

Application of machine learning techniques on the context of livestock analysis
af: Islam, Md. Shajedul, et al.
Udgivet: (2018)

Machine learning for stress prediction
af: Salehin, Sherajus, et al.
Udgivet: (2023)

Heart disease prediction using techniques of classification in machine learning
af: Afrose, Sadia, et al.
Udgivet: (2021)

Application of machine learning techniques on the context of predicting upcoming traffic congestion and providing the best preferred path
af: Saquib, Muhammad Sadman, et al.
Udgivet: (2019)

A voice signal based gender prediction model using random forest classifier
af: Ahmed, Saif, et al.
Udgivet: (2018)

Data analysis on the Bangladesh share market using Machine-Learning
af: Sadman, Syed Hassan, et al.
Udgivet: (2021)

Machine learning based stream selection of secondary school students in Bangladesh
af: Ahmad, Shabbir
Udgivet: (2024)

A supervised learning approach by machine learning and deep learning algorithms to predict type II DM risk
af: Farabe, Abdullah Al, et al.
Udgivet: (2021)

Performance analysis of different machine learning approaches for single modal facial expression detection
af: Zinia, Surovi, et al.
Udgivet: (2018)

Polycystic ovary syndrome detection using neural network.
af: Istiyaq, Tahsin, et al.
Udgivet: (2024)

Heart disease prediction system
af: Amit, Tayab Al Azad, et al.
Udgivet: (2022)

SCAMM: detection and prevention of SQL injection attacks using a machine learning approach
af: Alam, Auninda, et al.
Udgivet: (2021)

Identification of fake news using machine learning in distributed system
af: Saif, Mehruz, et al.
Udgivet: (2021)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
af: Rahee, Arnob, et al.
Udgivet: (2021)

Performance analysis of machine learning algorithms for Malware classification
af: Bushra, Raisa Hasan, et al.
Udgivet: (2023)

Forecasting stock market prices using advanced tools of machine learning
af: Anwar, Md. Tawhid, et al.
Udgivet: (2019)

Early detection of breast cancer using machine learning
af: Fuad, Wasi Mohammad
Udgivet: (2019)

A novel approach to reduce air pollution through machine learning based PM2.5 prediction
af: Alif, Omar Farhad, et al.
Udgivet: (2023)

Prediction of diabetes induced complications using different machine learning algorithms
af: Rahman, Tahsinur, et al.
Udgivet: (2018)

Nonparametric bootstrapping for multiple logistic regression model using R
af: Hossain, Ahmed, et al.
Udgivet: (2010)

Fraud detection in E-commerce using natural language processing
af: Kabir, Iftekhar, et al.
Udgivet: (2023)

Estimating flood susceptibility of Bangladesh in the future year using machine learning
af: Alim, Sakib Bin, et al.
Udgivet: (2021)

Early grade prediction using profile data
af: Iqbal, Sumaiya, et al.
Udgivet: (2021)

Machine learning based analysis and prediction of crop yield and prices of Aman, Aus and Boro rice
af: Bhattacharjee, Ruposri, et al.
Udgivet: (2024)

Predicting a T20 cricket match result while the match is in progress
af: Munir, Fahad, et al.
Udgivet: (2015)

Nonrecursive causal models /
af: Berry, William Dale
Udgivet: (1984)

Finding ideal geographical location for businesses using machine learning technique
af: Mahmud, Mir Ibtid, et al.
Udgivet: (2022)