Perform random forest repetitions.
Usage
rf(analysisTable, cls, params = list(), nreps = 100, seed = 1234)Arguments
- analysisTable
tibble of phenotype data suitable for random forest analysis as returned by
preparePhenotypeData- cls
analysisTable column to use as response vector. NULL for unsupervised analyses.
- params
additional arguments to pass to randomForest::randomForest
- nreps
number of repetitions
- seed
random number seed
Examples
library(dplyr)
## Retrieve file paths for example data
files <- list.files(system.file('phenotypeDataCollectionSheets',
package = 'pdi'),full.names = TRUE)
## Prepare data
d <- map(files,readPhenotypeSheet) %>%
map(preparePhenotypeData) %>%
bind_rows() %>%
siteAdjustment() %>%
mutate(`Live crown ratio (%)` = liveCrownRatio(`Total height (m)`,
`Lower crown height (m)`),
`Crown condition (%)` = crownCondition(`Missing crown (%)`,
`Crown transparency (%)`),
`Crown volume (m^3)` = crownVolume(`Crown radius (m)`,
`Total height (m)`,
`Lower crown height (m)`,
`Crown condition (%)`),
`Bleed prevalence (%)` = bleedPrevalence(`Active bleed length (mm)`,
`Active bleeds`,
`Black staining length (mm)`,
`Black staining`,
`Diameter at breast height (m)`),
`Agrilus exit hole density (m^-2)` = agrilusExitHoleDensity(`Agrilus exit holes`,
`Diameter at breast height (m)`)
)
t <- makeAnalysisTable(d)
## Generate random forest models
m <- rf(t,cls = NULL,nreps = 10)