Figure 2
From: Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning
Comparison of chronic wasting disease (CWD) status in free-ranging white-tailed deer in season-year 2020–21 between the CWD Prediction Web App and state surveillance data33. True Negatives (TNs) occurred when the CWD Prediction Web App prediction and the surveillance data agreed that CWD-status was CWD-non detect for the county in the season-year 2020–21. True Positives (TPs) occurred when the CWD Prediction Web App prediction and the surveillance data agreed that CWD-status was CWD-positive for the county in the season-year 2020–21. False Negatives (FNs) occurred when the CWD Prediction Web App predicted CWD-non detect, but the surveillance data declared CWD-positive for the county in season-year 2020–21. False Positives (FPs) occurred when the CWD Prediction Web App predicted CWD-positive, but the surveillance data declared CWD-non detect for the county in season-year 2020–21. Excluded represents counties omitted from predictions because harvest data was either not collected or could not be approximated by-county. Not Considered represents areas omitted from the Pooled Dataset33. Two sources of known error can cause predictions to deviate from reality: (1) model classification error and/or (2) error in CWD-status from surveillance. Specific to Minnesota, a third known error could cause predictions to deviate from reality: (3) error arising from the conversion of harvest data collected in Deer Permit Areas into county-approximations (see the Supplement for specific details). Map was created in QGIS (version 3.32.2-Lima)60.
