View source: R/plot_evaluation.R
plot_evaluation | R Documentation |
Plots the results of an spatial cross-validation performed with rf_evaluate()
.
plot_evaluation( model, fill.color = viridis::viridis( 3, option = "F", alpha = 0.8, direction = -1 ), line.color = "gray30", verbose = TRUE, notch = TRUE )
model |
A model resulting from |
fill.color |
Character vector with three hexadecimal codes (e.g. "#440154FF" "#21908CFF" "#FDE725FF"), or function generating a palette (e.g. |
line.color |
Character string, color of the line produced by |
verbose |
Logical, if |
notch |
Logical, if |
A ggplot.
rf_evaluate()
, get_evaluation()
, print_evaluation()
.
if(interactive()){ #loading example data data(plant_richness_df) data(distance_matrix) #fitting a random forest model rf.model <- rf( data = plant_richness_df, dependent.variable.name = "richness_species_vascular", predictor.variable.names = colnames(plant_richness_df)[5:21], distance.matrix = distance_matrix, distance.thresholds = 0, n.cores = 1, verbose = FALSE ) #evaluating the model with spatial cross-validation rf.model <- rf_evaluate( model = rf.model, xy = plant_richness_df[, c("x", "y")], n.cores = 1 ) #plotting the evaluation results plot_evaluation(rf.model) }
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