OMB Individually Reported
Markov random fields for mixed forests
Low riskExact public inventory row
Description
A level of uncertainty can exist in model predictions and sometimes that level of uncertainty is incorrectly assessed, leading to less effective decision-making when based on the model predictions.
Detailed example
Outputs include predicted species counts, presence/absence of species, and uncertainty intervals
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
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
These methods to correctly evaluate uncertainty in model predictions help stakeholders make more informed and effective decisions.
Controls / human review
ATO: No; PIA: Not published
Data needed
ForestGEO tree count data from the Republic of Palau