Census of Agriculture Propensity Scores via Machne Learning
Description
The Census of Agriculture is collected every 5 years and requires high participation levels from individuals and agricultural operations to provide relevant agricultural data to the nation.
Detailed example
The model outputs a probability score (all values from and including 0 to 1).
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
This model predicts how likely individuals or operations are to complete the Census of Agriculture. The predictions can help data collectors decide where they need to focus their efforts in order to get more complete census responses.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Information on the National Agriculture Statistics Service (NASS) list frame including previous survey response information, demographic information, as well as geospatial information.