RUSBoost.BEM: RUSBoost variant of BEMBoost

In nunompmoniz/ReBoost: Boosting by Resampling Approaches for Imbalanced Numerical Prediction Tasks

Description

RUSBoost variant of BEMBoost

Usage

RUSBoost.BEM(
  form,
  train,
  test,
  t_final = 100,
  BEM = 0.5,
  perc.U = 0.9,
  rel.thr = 0.9,
  coef = 1.5,
  ...
)

Arguments

form	The model formula.
train	A data.frame with the training data.
test	A data.frame with the test data.
t_final	The number of maximum boosting iterations. Default is 100.
BEM	Biggest error margin admissible. Defaults to 0.5.
perc.U	Percentage for Undersampling via Random Undersampling, i.e. percentage of cases with normal values to remain in the new dataset. Default is 0.9.
rel.thr	Relevance threshold. Default is 0.9.
coef	Coefficient used in boxplot statistics, which is used to create the relevance function. Default is 1.5.
...	Dots are passed to rpart

Value

Returns a vector with the predictions made by RUSBoost.BEM.

Examples

data(Boston,package="MASS")

idx <- sample(1:nrow(Boston),nrow(Boston)*0.75)
form <- medv ~ .

train <- Boston[idx,]
test <- Boston[-idx,]

preds <- RUSBoost.BEM(form,train,test)

nunompmoniz/ReBoost documentation built on Sept. 15, 2021, 8:28 p.m.