Showing content from https://cran.r-project.org/web/packages/randomForest/../tidypredict/vignettes/rf.R below:
## ----pre, include = FALSE----------------------------------------------------- if (!rlang::is_installed("randomForest")) { knitr::opts_chunk$set( eval = FALSE ) } ## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) library(dplyr) library(tidypredict) library(randomForest) library(parsnip) set.seed(100) ## ----------------------------------------------------------------------------- library(dplyr) library(tidypredict) library(randomForest) model <- randomForest(Species ~ ., data = iris, ntree = 100, proximity = TRUE) ## ----------------------------------------------------------------------------- getTree(model, labelVar = TRUE) %>% head() ## ----------------------------------------------------------------------------- tidypredict_fit(model)[1] ## ----------------------------------------------------------------------------- library(parsnip) parsnip_model <- rand_forest(mode = "classification") %>% set_engine("randomForest") %>% fit(Species ~ ., data = iris) tidypredict_fit(parsnip_model)[[1]]
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