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