BEMBoost: BEMBoost

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

Description

BEMBoost

Usage

BEMBoost(form, train, test, t_final = 100, BEM = 0.5, ...)

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.
...	Dots are passed to rpart

Value

Returns a vector with the predictions made by BEMBoost.

Examples

data(Boston,package="MASS")

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

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

preds <- BEMBoost(form,train,test)

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