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Activity Number: 337 - SPEED: Methodological Developments in Social Statistics, Part 1
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
Sponsor: Social Statistics Section
Abstract #307214
Title: Making Data-Driven Decisions About Serving Homeless Populations Using Machine Learning Tools
Author(s): Austin Lampros*
Keywords: Homeless; Non-profit; Statistical Learning

In the non-profit sector serving homeless populations, we want to better understand the factors and issues that impact individuals returning to homelessness after receiving care. For this research, I built a classification tree that showcases the most predictive factors and how they interact with each other. I then explored the factors that our organization can control and how that will impact the overall rates of returning to homelessness. In the end, this data-driven model gave my organization actionable ways of reducing the rate of returning to homelessness by changing some of our methods.

Authors who are presenting talks have a * after their name.

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