random_forest: random_forest Perform a classification or regression random...

In omu: A Metabolomics Analysis Tool for Intuitive Figures and Convenient Metadata Collection

random_forest Perform a classification or regression random forest model

Description

a wrapper built around the randomForest function from package randomForest. Returns a list with a randomForest object list, training data set, testing data set, metabolite metadata, and confusion matrices for training and testing data (if type was classification).

Usage

random_forest(
  count_data,
  metadata,
  model,
  training_proportion = c(80, 20),
  n_tree = 500
)

Arguments

count_data	Metabolomics data
metadata	sample data
model	a model of format variable ~.
training_proportion	a numeric vector of length 2, first element is the percent of samples to use for training the model, second element is the percent of samples used to test the models accuracy
n_tree	number of decision trees to create

Examples

rf_list <- random_forest(count_data = c57_nos2KO_mouse_countDF,metadata = c57_nos2KO_mouse_metadata,
model = Treatment ~.,training_proportion = c(60,40),n_tree = 500)

omu documentation built on Oct. 17, 2023, 1:06 a.m.