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Predicting Inequality of Opportunity and Poverty in India Using Machine Learning

This open-access book combines traditional economic methods with newer machine learning techniques such as regression trees and random forests to analyse data and provide an in-depth analysis of inequality of opportunity and poverty in India. Using data from national surveys and unique sources like...

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Main Authors: Mehta, Balwant Singh, Srivastava, Ravi, Dhote, Siddharth
Format: Online
Sprog:engelsk
Udgivet: Springer Nature 2025
Fag:
Inequality of Opportunity in India
Poverty Analysis
Machine Learning Techniques
Socio-Economic Disparities
Regional Inequality
Human Well-Being
Income Disparity
Health Equity
Educational Inequality
Data-Driven Research
Sustainable Development
Geo-Spatial Data
Online adgang:ONIX_20250513_9789819625444_25
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Summary:This open-access book combines traditional economic methods with newer machine learning techniques such as regression trees and random forests to analyse data and provide an in-depth analysis of inequality of opportunity and poverty in India. Using data from national surveys and unique sources like night-time satellite images and location data of points of interest, it explores different aspects of inequality and poverty. The book adopts a unique interdisciplinary approach, blending theories and methods from sociology, economics, geography, anthropology, and computer science to explore three key aspects of human well-being: income, health, and education, focusing on regional disparities. It aims to offer practical insights for policymakers and researchers who want to address social and economic inequalities in India.

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