TABLE 2.
Random forest algorithm results for training, testing, and full data
| True host | Test dataseta
|
True host | Training and test datasetb
|
True host | Complete datasetc
|
||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Predicted host |
Predicted host |
Predicted host |
|||||||||
| Human | Swine | Percent | Human | Swine | Percent | Human | Swine | Percent | |||
| Human | 12 | 2 | 85.7 | Human | 146 | 3 | 97.9 | Human | 3,038 | 150 | 95.3 |
| Swine | 0 | 15 | 100.0 | Swine | 4 | 145 | 97.3 | Swine | 4 | 145 | 97.3 |
a
The test data represents a randomly selected 10% of data separated from the initial random forest subset. These data were not used until after training had been performed.
b
The training and test data sets were combined and then rerun through the determined random forest algorithm to determine the accuracy of the model given the data.
c
The complete data set represents 100% of available data.