Homelessness service provision: A data science perspective

Keyphrases

• Data Science 100%
• Service Provision 100%
• Homeless Services 100%
• Homelessness 50%
• Reentry 50%
• United States 25%
• Propensity Score 25%
• Midwestern US 25%
• Machine Learning Techniques 25%
• Usage Patterns 25%
• Demographic Information 25%
• Housing Demand 25%
• Prevention Efforts 25%
• Publicly Funded 25%
• System Involvement 25%
• Random Forest 25%
• Administrative Dataset 25%
• Service Delivery 25%
• Prediction Task 25%
• Change Dynamics 25%
• Nearest Neighbor Matching 25%
• Homelessness Prevention 25%
• Public Service Provision 25%
• Service Usage 25%
• Service Information 25%

Computer Science

• Service Provision 100%
• Machine Learning Technique 50%
• Random Decision Forest 50%
• Prevention Effort 50%
• Service Delivery 50%
• Information Service 50%
• Initial Difference 50%
• United States of America 50%
• Proof 50%

Social Sciences

• Data Science 100%
• Reentry 66%
• Information Services 33%
• USA 33%
• Health Care Delivery 33%
• Propensity Score 33%
• Learning Method 33%
• Public Utilities 33%
• Household 33%
• Housing Needs 33%
• Random Forest 33%