SDMtune (version 0.1.0)

confMatrix: Confusion Matrix

Description

Computes Confusion Matrixes for threshold values varying from 0 to 1.

Usage

confMatrix(model, type = c("cloglog", "logistic"), test = NULL,
  th = NULL)

Arguments

model

'>SDMmodel object.

type

character. The output type, possible values are "cloglog" and "logistic", default is "cloglog".

test

'>SWD test locations, if not provided it uses the train dataset, default is NULL.

th

numeric vector, if provided it computes the evaluation at the given thresholds, default is NULL and it computes the evaluation for a sequence from 0 to 1.

Value

The Confusion Matrix for all the used thresholds.

Examples

# NOT RUN {
# Acquire environmental variables
files <- list.files(path = file.path(system.file(package = "dismo"), "ex"),
                    pattern = "grd", full.names = TRUE)
predictors <- raster::stack(files)

# Prepare presence locations
p_coords <- condor[, 1:2]

# Prepare background locations
bg_coords <- dismo::randomPoints(predictors, 5000)

# Create SWD object
presence <- prepareSWD(species = "Vultur gryphus", coords = p_coords,
                       env = predictors, categorical = "biome")
bg <- prepareSWD(species = "Vultur gryphus", coords = bg_coords,
                 env = predictors, categorical = "biome")

# Train a model
model <- train(method = "Maxnet", p = presence, a = bg, fc = "l")

# Get the confusion matrix for thresholds ranging from 0 to 1
cm <- confMatrix(model, type = "cloglog")
head(cm)
tail(cm)

# Get the confusion matrix for a specific threshold
confMatrix(model, type = "logistic", th = 0.6)
# }