ModelEvaluation | R Documentation |
Class to store results of model cross-validation with presence/absence (0/1) data
presence
:presence data used
absence
:absence data used
np
:number of presence points
na
:number of absence points
auc
:Area under the receiver operator (ROC) curve
pauc
:p-value for the AUC (for the Wilcoxon test W statistic
cor
:Correlation coefficient
pcor
:p-value for correlation coefficient
t
:vector of thresholds used to compute confusion matrices
confusion
:confusion matrices
prevalence
:Prevalence
ODP
:Overall diagnostic power
CCR
:Correct classification rate
TPR
:True positive rate
TNR
:True negative rate
FPR
:False positive rate
FNR
:False negative rate
PPP
:Positive predictive power
NPP
:Negative predictive power
MCR
:Misclassification rate
OR
:Odds-ratio
kappa
:Cohen's kappa
Robert J. Hijmans
Fielding, A. H. & J.F. Bell, 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24: 38-49
Liu, C., M. White & G. Newell, 2011. Measuring and comparing the accuracy of species distribution models with presence-absence data. Ecography 34: 232-243.
evaluate
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