Table 3. Evaluation metrics calculated on the test set and reported in percent (%) for biome predictions for each classifier.

Evaluation Metric	Classification model
	Logistic Regression	Linear Discriminant Analysis	Naive Bayes	Support Vector Machines	K-Nearest Neighbors	Decision Tree	Random Forests	Neural Networks
Accuracy	0.82	0.77	0.78	0.77	0.79	0.76	0.86	0.77
Precision	0.82	0.80	0.81	0.79	0.80	0.77	0.85	0.75
F1	0.81	0.79	0.78	0.75	0.79	0.75	0.85	0.76
Kappa	0.74	0.69	0.71	0.67	0.71	0.66	0.80	0.67

Recall foreach predicted vegetation type is calculated as the weighted number of correct predictions for a given known vegetation type. Precision for each predicted vegetation type is calculated as the weighted proportion of correctly classified vegetation unit to the sum of all predictions.