loocv_machine_learner: Apply loocv machine learning functions

In whamer/papros: PAthogen PROgnosis System

Description

This functions applies one or several machine learning methods on a given dataset and checks for the validity of the prediction

Usage

loocv_machine_learner(
  dataframe,
  aim_variable,
  co_variables,
  location = FALSE,
  method = c("DT", "BDT", "RF"),
  additionalparameters = FALSE,
  auto = FALSE
)

Arguments

dataframe	dataframe containing variables of interest
aim_variable	Character string with the name of the aim variable
co_variables	Character string with the name of the co-variables
location	defalut = FALSE; Character string with the name of the location. If FALSE each observation is treated as unique location
method	default = c("DT","BDT","RF"); which method should be used: DecisionTree, BoostedDecisionTree and/or RandomForest?
additionalparameters	default = FALSE; list containing additional parameters for the ML procedures / e.g.: list(RF=list(ntree=10000))
auto	default = FALSE; boolean operator defining if "machine_learner" or "auto_machine_learner" should be used

Value

list containing the models

Author(s)

Wolfgang Hamer

whamer/papros documentation built on Feb. 6, 2021, 8:54 a.m.