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## ----load species-------------------------------------------------------------
library(OpenRange)
pcontorta <- OpenRange_load_species(species = "Pinus contorta")
plot(pcontorta[2])
## ----get metadata-------------------------------------------------------------
library(tidyverse)
# Grab the stats
model_stats <- OpenRange_get_stats()
# Reformat them into a single table
model_stats_wide <- bind_rows(model_stats$rangebagging %>%
mutate(algorithm = "rangebagging"),
model_stats$ppm %>%
mutate(algorithm = "ppm"),
model_stats$points %>%
mutate(algorithm = "points"))
# Get relevant model stats
model_stats_wide %>%
filter(model_id == pcontorta$model_id)->test
test %>%
select(cv_mean_train_npresence,cv_mean_test_n_presence,cv_mean_test_auc,cv_mean_train_auc)
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