Ensemble.SDM-class: An S4 class to represent an ensemble SDM

In hugocalcad/LigthSSDM: Optimized SSDM Package for large dataset

Description

This is an S4 class to represent an ensemble SDM from multiple algorithms (including generalized linear model, general additive model, multivariate adaptive splines, generalized boosted regression model, classification tree analysis, random forest, maximum entropy, artificial neural network, and support vector machines). This S4 class is returned by ensemble_modelling or ensemble.

Slots

uncertainty

raster. Between-algorithm variance map.

algorithm.correlation

data frame. Between-algorithm correlation matrix.

algorithm.evaluation

data frame. Evaluation of the ensemble SDM (available metrics include AUC, Kappa, sensitivity, specificity and proportion of correctly predicted occurrences) and identification of the optimal threshold to convert the habitat suitability map into a binary presence/absence map.

See Also

Algorithm.SDM an S4 class to represent an SDM based on a single algorithm, and Stacked.SDM an S4 class for SSDMs.

hugocalcad/LigthSSDM documentation built on June 22, 2019, 12:43 a.m.