plot_tuning: Plots a tuning object produced by 'rf_tuning()'

In BlasBenito/spatialRF: Easy Spatial Modeling with Random Forest

Plots a tuning object produced by rf_tuning()

Description

Plots the tuning of the hyperparameters num.trees, mtry, and min.node.size performed by rf_tuning().

Usage

plot_tuning(
  model,
  point.color = viridis::viridis(
    100,
    option = "F"
  ),
  verbose = TRUE
)

Arguments

model	A model fitted with rf_tuning(). Default: NULL
point.color	Colors of the plotted points. Can be a single color name (e.g. "red4"), a character vector with hexadecimal codes (e.g. "#440154FF" "#21908CFF" "#FDE725FF"), or function generating a palette (e.g. viridis::viridis(100)). Default: viridis::viridis(100, option = "F")
verbose	Logical, if TRUE, the plot is printed. Default: TRUE

Value

A ggplot.

See Also

rf_tuning()

Examples

if(interactive()){

#load example data
data(plant_richness_df)

#fit 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
)

#tune random forest model
rf.model <- rf_tuning(
 model = rf.model,
 xy = plant_richness_df[, c("x", "y")],
 n.cores = 1,
 verbose = FALSE
)

#generate tuning plot
plot_tuning(model = rf.model)

}

BlasBenito/spatialRF documentation built on Sept. 1, 2022, 1:42 p.m.