. Author manuscript; available in PMC: 2017 Dec 9.

Published in final edited form as: J Med Entomol. 2016 Jun 9:tjw076. doi: 10.1093/jme/tjw076

Table 4. Model selection criteria and performance metrics for the models selected for each modeling algorithm used in the ensemble model of Ixodes pacificus distribution.

Model selection	GLM^a		MARS^b		Maxent^a		RF^a

Performance metric	Test split	Train	Test split	Train	Test split	Train	Test split	Train
AUC^c	0.95	0.98	0.94	0.97	0.94	0.97	0.95	0.93
Percent correctly classified	89.9	90.8	89.2	92.4	89.1	92.0	92.5	89.5
Sensitivity	0.91	0.91	0.88	0.93	0.90	0.92	0.89	0.89
Specificity	0.89	0.91	0.90	0.92	0.89	0.92	0.95	0.90
Mean threshold	0.35	0.26	0.33	0.31	0.30	0.27	0.49	0.42

Candidate variables (predictor set 1): Bio6, Bio19, Bio3, Bio18, Bio8, Bio9, Bio2, GDD12Cum, Bio5, PercForest, Vp7.

Candidate variables (predictor set 2): Bio15, Bio19, Bio1, Bio17, Bio8, Vp10, GDD2Cum, PercForest.

Area under the (ROC) curve.

GLM, generalized linear model; MARS, multivariate adaptive regression spline; Maxent, maximum entropy; RF, random forest.